Medien Wiki - User contributions [en]

GMU:Techniken des Virtuellen/Kei Kitamura

2017-09-24T16:26:13Z

Kei kitamura:

==[[Kei Kitamura]]: Himorogi==
 
[[File:KK_Himorogi_scene02_02.png||500px]]
 
Concept 
Himorogi is a virtual installation to experiment possibility of visual phenomena in virtual environment, 
especially, the look of the space. 
This is inspired by “shinto”, a kind of primitive aminism in Japan, 
since it has a tradition to surround spaces around the objects of faith. 
Some of those objects are recognized as a “god”, others are a temporal “avatar” for a “god”. 
The first one is called “Iwakura”, and another one is “Himorogi”. 
Additionally, primitive rituals are the origin of various form of events, arts, entertainments. 
Head mounted display based contents are also on this context . 
Therefore, I aimed to realize the effects on the look in this environment, 
which has a space believed that it has a spiritual power, and is sometimes feared. 

[https://vimeo.com/226302957 Video documentation]
 
[https://vimeo.com/227530148 Gameplay]

GMU:Techniken des Virtuellen/Kei Kitamura

2017-09-24T16:26:02Z

Kei kitamura:

==[[Kei Kitamura]]: Himorogi==
 
[[File:KK_Himorogi_scene02_02.png||500px]]
Concept 
Himorogi is a virtual installation to experiment possibility of visual phenomena in virtual environment, 
especially, the look of the space. 
This is inspired by “shinto”, a kind of primitive aminism in Japan, 
since it has a tradition to surround spaces around the objects of faith. 
Some of those objects are recognized as a “god”, others are a temporal “avatar” for a “god”. 
The first one is called “Iwakura”, and another one is “Himorogi”. 
Additionally, primitive rituals are the origin of various form of events, arts, entertainments. 
Head mounted display based contents are also on this context . 
Therefore, I aimed to realize the effects on the look in this environment, 
which has a space believed that it has a spiritual power, and is sometimes feared. 

[https://vimeo.com/226302957 Video documentation]
 
[https://vimeo.com/227530148 Gameplay]

GMU:Techniken des Virtuellen/Kei Kitamura

2017-09-24T16:25:40Z

Kei kitamura:

==[[Kei Kitamura]]: Himorogi==
 
[[File:KK_Himorogi_scene02_02.png]]
Concept 
Himorogi is a virtual installation to experiment possibility of visual phenomena in virtual environment, 
especially, the look of the space. 
This is inspired by “shinto”, a kind of primitive aminism in Japan, 
since it has a tradition to surround spaces around the objects of faith. 
Some of those objects are recognized as a “god”, others are a temporal “avatar” for a “god”. 
The first one is called “Iwakura”, and another one is “Himorogi”. 
Additionally, primitive rituals are the origin of various form of events, arts, entertainments. 
Head mounted display based contents are also on this context . 
Therefore, I aimed to realize the effects on the look in this environment, 
which has a space believed that it has a spiritual power, and is sometimes feared. 

[https://vimeo.com/226302957 Video documentation]
 
[https://vimeo.com/227530148 Gameplay]

File:KK Himorogi scene02 02.png

2017-09-24T16:25:18Z

Kei kitamura:

== Summary ==

== Copyright status: ==

== Source: ==

GMU:Techniken des Virtuellen/Kei Kitamura

2017-09-24T16:22:21Z

Kei kitamura:

==[[Kei Kitamura]]: Himorogi==
 

Concept 
Himorogi is a virtual installation to experiment possibility of visual phenomena in virtual environment, 
especially, the look of the space. 
This is inspired by “shinto”, a kind of primitive aminism in Japan, 
since it has a tradition to surround spaces around the objects of faith. 
Some of those objects are recognized as a “god”, others are a temporal “avatar” for a “god”. 
The first one is called “Iwakura”, and another one is “Himorogi”. 
Additionally, primitive rituals are the origin of various form of events, arts, entertainments. 
Head mounted display based contents are also on this context . 
Therefore, I aimed to realize the effects on the look in this environment, 
which has a space believed that it has a spiritual power, and is sometimes feared. 

[https://vimeo.com/226302957 Video documentation]
 
[https://vimeo.com/227530148 Gameplay]

GMU:Techniken des Virtuellen/Kei Kitamura

2017-09-24T16:21:18Z

Kei kitamura:

Concept 
Himorogi is a virtual installation to experiment possibility of visual phenomena in virtual environment, 
especially, the look of the space. 
This is inspired by “shinto”, a kind of primitive aminism in Japan, 
since it has a tradition to surround spaces around the objects of faith. 
Some of those objects are recognized as a “god”, others are a temporal “avatar” for a “god”. 
The first one is called “Iwakura”, and another one is “Himorogi”. 
Additionally, primitive rituals are the origin of various form of events, arts, entertainments. 
Head mounted display based contents are also on this context . 
Therefore, I aimed to realize the effects on the look in this environment, 
which has a space believed that it has a spiritual power, and is sometimes feared. 

[https://vimeo.com/226302957 Video documentation]
 
[https://vimeo.com/227530148 Gameplay]

GMU:Techniken des Virtuellen/Kei Kitamura

2017-08-02T07:49:08Z

Kei kitamura:

[https://vimeo.com/226302957 Video documentation]
 
[https://vimeo.com/227530148 Gameplay]

GMU:Techniken des Virtuellen/Kei Kitamura

2017-08-02T07:48:51Z

Kei kitamura:

[https://vimeo.com/226302957| Video documentation]
 
[https://vimeo.com/227530148| Gameplay]

GMU:Techniken des Virtuellen/Kei Kitamura

2017-08-02T07:48:23Z

Kei kitamura:

[https://vimeo.com/226302957 | Video documentation]
 
[https://vimeo.com/227530148 | Gameplay]

GMU:Techniken des Virtuellen/Kei Kitamura

2017-08-02T07:47:28Z

Kei kitamura:

[https://vimeo.com/226302957| Video documentation]
 
[https://vimeo.com/227530148| Gameplay]

GMU:Techniken des Virtuellen/Kei Kitamura

2017-08-02T07:46:15Z

Kei kitamura: Created page with "[Video documentation|https://vimeo.com/226302957] [Gameplay|https://vimeo.com/227530148]"

[Video documentation|https://vimeo.com/226302957]
[Gameplay|https://vimeo.com/227530148]

GMU:Techniken des Virtuellen

2017-08-02T07:44:34Z

Kei kitamura:

Lecturer: [https://www.uni-weimar.de/kunst-und-gestaltung/wiki/Jörg_Brinkmann Jörg Brinkmann] 
Credits: 6 ECTS, 4 SWS 
Date: Thursdays 17:00-20:30 
Venue: Performance Platform, Digital Bauhaus Lab (Room 001) 
First meeting: Thursday, April 13th 2017, 17:00 

 

''“In today’s society, where drones are used for warfare and romantic relationships begin online can we any longer distinguish between the so-called real and the virtual?”'' (Cécile B. Evans)

Everyone talks about VR nowadays, but aren’t sites like Facebook and Instagram already their own form of virtual reality being fed on a daily basis by disembodied snippets of our lives? Do we have to worry that soon the real world will be in second place?

In this course, we will be inspired and challenged by different artistic approaches that embrace “the virtual” as a concept, aesthetic, or technique. We will start by using simple methods to help amplify and channel our ideas and concepts through media and technology. Furthermore, we will use Unity 3D to create our very own virtual worlds, objects, or avatars which will include integrating virtual reality devices like the HTC VIVE. This course involves working with, but is not limited to, the Performance Platform at the Digital Bauhaus Lab.

'''BLOCKMODUL 1 – VIRTUAL MINDSCAPES''' 
Date: 18. - 20.05.2017, starting at 14:00 
Space: Room 204, Marienstrasse 7b

Please download this Software before: 
Unity 3D: https://store.unity.com/download?ref=personal 
Blender: https://www.blender.org/download/ 
MeshMixer: http://www.meshmixer.com/download.html 
MakeHuman: http://www.makehuman.org/download.php 

'''HOMEWORK FOR THURSDAY 18th of MAY: create a "virtual walk" on your computer in form of a "video-essay"''' 
If u want to record both screen and sound with osx, win or linux i found this great software that works without Soundflower:
https://obsproject.com

'''PREREQUISITES''' 
No previous programming experience required.

'''CRITERIA FOR PASSING''' 
In order to successfully participate you will have to develop and document your own project that can be in the form of a performance, video work or installation for example. Also, regularly attend to the sessions and participation is mandatory.

'''LANGUAGE''' 
The course will be in English, unless all participants are speaking German.

'''APPLICATION''' 
Please send a motivation letter before April 10th, 2017 to [mailto:joerg.brinkmann@uni-weimar.de joerg.brinkmann@uni-weimar.de]

Subject: Techniken des Virtuellen

Content:
* Your motivation to join the course
* If you have a portfolio, webpage or any links or PDFs of your own projects, please attach them. It doesn't have to relate to the class
* Name, Surname
* program and semester (Studienprogramm und Fachsemester)
* matriculation number (Matrikelnummer)

'''~A FEW THINGS THAT MIGHT BE INSPIRING~'''

'''ARTISTS'''

Cécile B. Evans interview: The Virtual is Real 
https://www.youtube.com/watch?v=nDe_W11KY4c

A Conversation with Jon Rafman 
https://vimeo.com/11685295

Jeremy Bailey - The Future of Television (2012) 
https://www.youtube.com/watch?v=pClOufl12r8

Aram Bartholl - Hurt me plenty (2014) 
http://www.aqnb.com/2014/09/25/aram-bartholl-hurt-me-plenty-2014-exhibition-photos/

Ed Atkins on his hyper-real and harrowing new films 
http://www.dazeddigital.com/artsandculture/article/34547/1/ed-atkins-hyper-real-harrowing-new-films-hisser-safe-conduct-corpsing

Constant Dullaart - 100,000 Followers for Everyone! 
http://dismagazine.com/dystopia/67039/constant-dullaart-100000-followers-for-everyone/

Artificial Ecology: Ian Cheng on the Strange Art of Simulating Life, and the Conceptual Merits of Pokémon Go 
http://www.artspace.com/magazine/interviews_features/art-bytes/ian-cheng-interview-54128

Petra Cortwright - ✝✝LA.christening vid.move,df ✝Movie on 2013-02-05 at 19.25.mov 
https://www.youtube.com/watch?v=84h8pLW1xmE

Martin Kohout - Sjezd 
http://aqnb.com/uploads/sjezd.html

Die Künstlerin Morehshin Allahyari baut im 3D-Drucker zerstörte Kunst nach 
http://sz-magazin.sueddeutsche.de/texte/anzeigen/44419/Wir-haben-die-Moeglichkeit-Dinge-auferstehen-zu-lassen

Rosa Menkman - DCT:SYPHONING. The 1000000th interval (The 64th interval). 
https://vimeo.com/176773197

Cory Arcangel: Pro Tools: Various Self Playing Bowling Games, 2011 
https://www.youtube.com/watch?v=N5UGN7tq1lQ

Woody Vasulka & Brian O'Reilly - Scan Processor Studies 
https://www.youtube.com/watch?v=De4DWMyQBfU

'''BOOKS'''

Domenico Quaranta - Beyond New Media Art (PDF) 
http://www.linkartcenter.eu/public/editions/Domenico_Quaranta_Beyond_New_Media_Art_Link_Editions_ebook_2013.pdf

Jack Burnham - Beyond Modern Sculpture: The Effects of Science and Technology on the Sculpture of this Century (PDF) 
https://sculptureatpratt.files.wordpress.com/2015/07/jack-burnham-beyond-modern-sculpture.pdf

Haunted Media: Electronic Presence from Telegraphy to Television (ISBN 0822325535, Limona Steubenstraße 8) 
https://www.dukeupress.edu/haunted-media

Art and the Internet (ISBN 9781907317989 , Limona Steubenstraße 8) 
http://netartnet.net/news/announcement/item/779-book-release-art-and-the-internet

'''PROJECTS'''

*[[/Jörg Brinkmann|Jörg Brinkmann - Place Beneath Past 2017]]
*[[/Kei Kitamura|Kei Kitamura - Himorogi]]

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-31T06:29:46Z

Kei kitamura:

== Concept==
Flow of graphics 
 
This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external variables, which came from other Pure data / max patch. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look of texture by visual effects. 
 
 

==Files==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch to get more complexed result. 
 
 
3.Select key color for masking 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
You can select a key color for chroma key with a window with red lines. 
Either of black or white part of the noise map is selected, and the selected color becomes transparent. 
The setting of key color is assigned for both two noise textures. 
 
 
4.Chroma key 
[[File: KK_dataflow_step4.png|200px|thumb|left]][[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
The alpha channel of noise map is assigned for the alpha channel of a video from webcam. 
Now the video is partially transparent. 
 
 
5.Transformation 
[[File: KK_dataflow_step5.png|200px|thumb|left]][[File: KK_dataflow_offset.png|200px|thumb|left]] 
Final composition consists of a original video as a background, and two edited layer with external alpha channel. 
To deform the video, the edited two layer must be transformed. 
In this case, scale and offset is varied. 
 
 
6.Composition 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
Layers are composited with "jit.alphablend" node, so that the background video can be seen in the transparent area of upper layers. 
 
 

==Result==
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-31T06:28:48Z

Kei kitamura:

== Concept==
Flow of graphics 
 
This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external variables, which came from other Pure data / max patch. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look of texture by visual effects. 
 
 

==File==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch to get more complexed result. 
 
 
3.Select key color for masking 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
You can select a key color for chroma key with a window with red lines. 
Either of black or white part of the noise map is selected, and the selected color becomes transparent. 
The setting of key color is assigned for both two noise textures. 
 
 
4.Chroma key 
[[File: KK_dataflow_step4.png|200px|thumb|left]][[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
The alpha channel of noise map is assigned for the alpha channel of a video from webcam. 
Now the video is partially transparent. 
 
 
5.Transformation 
[[File: KK_dataflow_step5.png|200px|thumb|left]][[File: KK_dataflow_offset.png|200px|thumb|left]] 
Final composition consists of a original video as a background, and two edited layer with external alpha channel. 
To deform the video, the edited two layer must be transformed. 
In this case, scale and offset is varied. 
 
 
6.Composition 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
Layers are composited with "alpha blend" node, so that the background video can be seen in the transparent area of upper layers. 
 
 

==Result==
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-31T06:27:03Z

Kei kitamura: /* Methods */

== Concept==
Flow of graphics 
 
This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external variables, which came from other Pure data / max patch. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look of texture by visual effects. 
 
 

==File==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch to get more complexed result. 
 
 
3.Select key color for masking 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
You can select a key color for chroma key with a window with red lines. 
Either of black or white part of the noise map is selected, and the selected color becomes transparent. 
The setting of key color is assigned for both two noise textures. 
 
 
4.Chroma key 
[[File: KK_dataflow_step4.png|200px|thumb|left]][[File: KK_chromakey.png|200px|thumb|left]] 
The alpha channel of noise map is assigned for the alpha channel of a video from webcam. 
Now the video is partially transparent. 
 
 
5.Transformation 
[[File: KK_dataflow_step5.png|200px|thumb|left]][[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
Final composition consists of a original video as a background, and two edited layer with external alpha channel. 
To deform the video, the edited two layer must be transformed. 
In this case, scale and offset is varied. 
 
 
6.Composition 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
Layers are composited with "alpha blend" node, so that the background video can be seen in the transparent area of upper layers. 
 
 

==Result==
[[File: KK_dataflow_offset.png|200px|thumb|left]] 
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

File:KK dataflow step6.png

2017-03-31T06:26:45Z

Kei kitamura: File uploaded with MsUpload

File uploaded with MsUpload

File:KK dataflow step4.png

2017-03-31T06:21:56Z

Kei kitamura: Kei kitamura uploaded a new version of File:KK dataflow step4.png

File uploaded with MsUpload

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-31T06:20:59Z

Kei kitamura:

== Concept==
Flow of graphics 
 
This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external variables, which came from other Pure data / max patch. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look of texture by visual effects. 
 
 

==File==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch to get more complexed result. 
 
 
3.Select key color for masking 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
You can select a key color for chroma key with a window with red lines. 
Either of black or white part of the noise map is selected, and the selected color becomes transparent. 
The setting of key color is assigned for both two noise textures. 
 
 
4.Chroma key 
[[File: KK_dataflow_step4.png|200px|thumb|left]][[File: KK_chromakey.png|200px|thumb|left]] 
The alpha channel of noise map is assigned for the alpha channel of a video from webcam. 
Now the video is partially transparent. 
 
 
5.Transformation 
[[File: KK_dataflow_step5.png|200px|thumb|left]][[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
Final composition consists of a original video as a background, and two edited layer with external alpha channel. 
To deform the video, the edited two layer must be transformed. 
In this case, scale and offset is varied. 
 
 

==Result==
[[File: KK_dataflow_offset.png|200px|thumb|left]] 
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

File:KK dataflow step5.png

2017-03-31T06:20:46Z

Kei kitamura: File uploaded with MsUpload

File uploaded with MsUpload

File:KK dataflow step4.png

2017-03-31T06:18:06Z

Kei kitamura: File uploaded with MsUpload

File uploaded with MsUpload

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-31T06:12:41Z

Kei kitamura: /* Methods */

== Concept==
Flow of graphics 
 
This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external variables, which came from other Pure data / max patch. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look of texture by visual effects. 
 
 

==File==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch to get more complexed result. 
 
 
3.Select key color for masking 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
You can select a key color for chroma key with a window with red lines. 
Either of black or white part of the noise map is selected, and the selected color becomes transparent. 
The setting of key color is assigned for both two noise textures. 
 
 
4.Chroma key 
The alpha channel of noise map is assigned for the alpha channel of a video from webcam. 
Now the video is partially transparent. 
 
 
5.Transformation 
Final composition consists of a original video as a background, and two edited layer with external alpha channel. 
To deform the video, the edited two layer must be transformed. 
In this case, scale and offset is varied. 
 
 

==Result==
[[File: KK_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_offset.png|200px|thumb|left]] 
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-31T06:07:02Z

Kei kitamura: /* Methods */

== Concept==
Flow of graphics 
 
This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external variables, which came from other Pure data / max patch. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look of texture by visual effects. 
 
 

==File==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch to get more complexed result. 
 
 
3.Select key color for masking 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
You can select a key color for chroma key with a window with red lines. 
Either of black or white part of the noise map is selected, and the selected color becomes transparent. 
The setting of key color is assigned for both two noise textures. 
 
 
4.Chroma key 
The alpha channel of noise map is assigned for the alpha channel of a video from webcam. 
Now the video is partially transparent. 
 
 
5.Composition 

 
 

==Result==
[[File: KK_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_offset.png|200px|thumb|left]] 
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-31T06:02:31Z

Kei kitamura: /* Methods */

== Concept==
Flow of graphics 
 
This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external variables, which came from other Pure data / max patch. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look of texture by visual effects. 
 
 

==File==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch. 
 
 
3.Select key color for masking 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
You can select a key color for chroma key with a window with red lines. 
Either of black or white part of the noise map is selected, and the selected color becomes transparent. 
The setting of key color is assigned for both two noise textures. 
 
 
4.Chroma key 

==Result==
[[File: KK_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_offset.png|200px|thumb|left]] 
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-23T17:06:25Z

Kei kitamura:

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-23T17:00:04Z

Kei kitamura: /* Concept */

== Concept==

This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external variables, which came from other Pure data / max patch. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look of texture by visual effects. 
 
 

==File==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch. 
 
 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
 
 

==Result==
[[File: KK_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_offset.png|200px|thumb|left]] 
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-23T16:29:17Z

Kei kitamura: /* Concept */

== Concept==

This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external multiple 2D coordinates. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look of texture by visual effects. 
 
 

==File==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch. 
 
 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
 
 

==Result==
[[File: KK_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_offset.png|200px|thumb|left]] 
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

GMU:Meandering through Space/Kei Kitamura

2017-03-14T08:11:24Z

Kei kitamura: /* Semester project */

[[User:Kei_kitamura]]
 
== Week 01 ==
[http://codepen.io/kayk5654/pen/LbjJmo Representation of the curve drawing instruction] 
The drawing instruction is [[File:Drawaline.pdf|here]]
[[Image:KK_firstcurve.png|thumb|left|200px]] 
 
 

== Week 03 ==

1. [https://codepen.io/kayk5654/pen/eBpKyY random distribution function] 
[[Image:KK_randomness.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/ZBbRXz curve controlled by randomness] 
[[Image:KK_randomwalk.png|thumb|left|200px]] 
 
 
== Week 04 ==

1. [https://codepen.io/kayk5654/pen/woMQZv turtle walk] 
The curve shows the turning point of the turtle. 
[[Image:KK_turtle01.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/mOVQgo turtle walk with data] 
The selected background image is converted to the command which defines the direction of turtle walk. 
Each pixels of the image are sampled, and the strongest one of the R, G or B is assigned as a command. 
Thus, the direction of the curve reflects the dominant color factor 
To test locally, you can download this project; 
[[Media:Turtle_homework_02_modified.zip]] 
[[Image:KK_turtle02.png|thumb|left|200px]] 
 
 

== Week 05 ==

1. [https://codepen.io/kayk5654/pen/VmWEgy recursive curve] 
[[Image:KK_fractal01.png|thumb|left|200px]] 
 

2. [https://codepen.io/kayk5654/pen/ObgBda L-system] 
[[Image:KK_fractal2.png|thumb|left|200px]] 
 
 

== Week 06 ==

[https://codepen.io/kayk5654/pen/wgaYjW breitenberg vehicle] 
Each vehicles prefer either of red, green or blue lights. 
You can drag the lights by keep pressing the central point of the light. 
[[Image:KK_breitenberg_vehicle1.png|thumb|left|200px]] 
 
 

== Week 07 ==

[https://codepen.io/kayk5654/pen/ygQGBP breitenberg vehicle with custom environment] 
Vehicles draw streaks with brushes. 
Each vehicles prefers either of dark area or bright area of their environment. 
 
[https://codepen.io/kayk5654/pen/ZLqPKX My original sketch] uses external .png file as brushes. 
You can download .zip and test it with your own brush image on your local editor. 
[[Media:Breitenberg_vehicle_homework_1.zip]] 
[[Image:KK_breitenberg_vehicle2.png|thumb|left|200px]] 
 

 

== Week 10 ==

[https://codepen.io/kayk5654/pen/vggavj magnetic matrix] 
Needles moves continuously by the influence of the noise field. 
When you drag on the needles, they create circular pattern around the mouse pointer. 
[[Image:KK_magnetrix.png|thumb|left|200px]] 
 
 

== Week 11/12 ==

[https://codepen.io/kayk5654/pen/oBBMOp soundfun] 
This sketch has 4 visualization functions. 
"drawLevel" shows the loudness of the sound. 
"drawWaveform" and "drawFFT" shows waveform and the result of FFT analysis. 
"drawOsci" shows waveforms of audio input from the mic of your computer 
Also, there are different functional sounds assigned 1 - 6 keys on your keyboard. 
[[Image:KK_soundfun.png|thumb|left|200px]] 
 
 

== Semester project ==
 
I have tried to generate curves on the surface of 3d model, so that the curvy patterns of mesh forms 3d object. 
The idea comes from Japanese traditional patterns of [http://bit.ly/2llmlqD water flow] , 
and I'd like to get smilar result by adjusting parameters of noise. 
 
Work in progress: 
 
 
[[:File:curve generation test 02.zip]] 
[[File:KK_meandering_wip1.png|200px|thumb|left]] 
 
 
[[:File:curve generation test 04.zip]] 
[[File:KK_meandering_wip2.png|200px|thumb|left]] 
[[File:KK_meandering_wip3.png|200px|thumb|left]] 
 
 
[[:File:curve generation test 05.zip]] 
[[File:KK_meandering_wip4.png|200px|thumb|left]] 
[[File:KK_meandering_wip5.png|200px|thumb|left]] 
 
 
Reference: 
[https://threejs.org/ three.js] 
[https://github.com/spite/THREE.MeshLine THREE.Meshline]

File:Curve generation test 02.zip

2017-03-14T08:11:14Z

Kei kitamura: File uploaded with MsUpload

File uploaded with MsUpload

GMU:Meandering through Space/Kei Kitamura

2017-03-14T08:09:35Z

Kei kitamura: /* Semester project */

[[User:Kei_kitamura]]
 
== Week 01 ==
[http://codepen.io/kayk5654/pen/LbjJmo Representation of the curve drawing instruction] 
The drawing instruction is [[File:Drawaline.pdf|here]]
[[Image:KK_firstcurve.png|thumb|left|200px]] 
 
 

== Week 03 ==

1. [https://codepen.io/kayk5654/pen/eBpKyY random distribution function] 
[[Image:KK_randomness.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/ZBbRXz curve controlled by randomness] 
[[Image:KK_randomwalk.png|thumb|left|200px]] 
 
 
== Week 04 ==

1. [https://codepen.io/kayk5654/pen/woMQZv turtle walk] 
The curve shows the turning point of the turtle. 
[[Image:KK_turtle01.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/mOVQgo turtle walk with data] 
The selected background image is converted to the command which defines the direction of turtle walk. 
Each pixels of the image are sampled, and the strongest one of the R, G or B is assigned as a command. 
Thus, the direction of the curve reflects the dominant color factor 
To test locally, you can download this project; 
[[Media:Turtle_homework_02_modified.zip]] 
[[Image:KK_turtle02.png|thumb|left|200px]] 
 
 

== Week 05 ==

1. [https://codepen.io/kayk5654/pen/VmWEgy recursive curve] 
[[Image:KK_fractal01.png|thumb|left|200px]] 
 

2. [https://codepen.io/kayk5654/pen/ObgBda L-system] 
[[Image:KK_fractal2.png|thumb|left|200px]] 
 
 

== Week 06 ==

[https://codepen.io/kayk5654/pen/wgaYjW breitenberg vehicle] 
Each vehicles prefer either of red, green or blue lights. 
You can drag the lights by keep pressing the central point of the light. 
[[Image:KK_breitenberg_vehicle1.png|thumb|left|200px]] 
 
 

== Week 07 ==

[https://codepen.io/kayk5654/pen/ygQGBP breitenberg vehicle with custom environment] 
Vehicles draw streaks with brushes. 
Each vehicles prefers either of dark area or bright area of their environment. 
 
[https://codepen.io/kayk5654/pen/ZLqPKX My original sketch] uses external .png file as brushes. 
You can download .zip and test it with your own brush image on your local editor. 
[[Media:Breitenberg_vehicle_homework_1.zip]] 
[[Image:KK_breitenberg_vehicle2.png|thumb|left|200px]] 
 

 

== Week 10 ==

[https://codepen.io/kayk5654/pen/vggavj magnetic matrix] 
Needles moves continuously by the influence of the noise field. 
When you drag on the needles, they create circular pattern around the mouse pointer. 
[[Image:KK_magnetrix.png|thumb|left|200px]] 
 
 

== Week 11/12 ==

[https://codepen.io/kayk5654/pen/oBBMOp soundfun] 
This sketch has 4 visualization functions. 
"drawLevel" shows the loudness of the sound. 
"drawWaveform" and "drawFFT" shows waveform and the result of FFT analysis. 
"drawOsci" shows waveforms of audio input from the mic of your computer 
Also, there are different functional sounds assigned 1 - 6 keys on your keyboard. 
[[Image:KK_soundfun.png|thumb|left|200px]] 
 
 

== Semester project ==
 
I have tried to generate curves on the surface of 3d model, so that the curvy patterns of mesh forms 3d object. 
The idea comes from Japanese traditional patterns of [http://bit.ly/2llmlqD water flow] , 
and I'd like to get smilar result by adjusting parameters of noise. 
 
Work in progress: 
[[File:KK_meandering_wip1.png|200px|thumb|left]] 
 
 
[[:File:curve generation test 04.zip]] 
[[File:KK_meandering_wip2.png|200px|thumb|left]] 
[[File:KK_meandering_wip3.png|200px|thumb|left]] 
 
 
[[:File:curve generation test 05.zip]] 
[[File:KK_meandering_wip4.png|200px|thumb|left]] 
[[File:KK_meandering_wip5.png|200px|thumb|left]] 
 
 
Reference: 
[https://threejs.org/ three.js] 
[https://github.com/spite/THREE.MeshLine THREE.Meshline]

GMU:Meandering through Space/Kei Kitamura

2017-03-14T08:09:04Z

Kei kitamura: /* Semester project */

[[User:Kei_kitamura]]
 
== Week 01 ==
[http://codepen.io/kayk5654/pen/LbjJmo Representation of the curve drawing instruction] 
The drawing instruction is [[File:Drawaline.pdf|here]]
[[Image:KK_firstcurve.png|thumb|left|200px]] 
 
 

== Week 03 ==

1. [https://codepen.io/kayk5654/pen/eBpKyY random distribution function] 
[[Image:KK_randomness.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/ZBbRXz curve controlled by randomness] 
[[Image:KK_randomwalk.png|thumb|left|200px]] 
 
 
== Week 04 ==

1. [https://codepen.io/kayk5654/pen/woMQZv turtle walk] 
The curve shows the turning point of the turtle. 
[[Image:KK_turtle01.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/mOVQgo turtle walk with data] 
The selected background image is converted to the command which defines the direction of turtle walk. 
Each pixels of the image are sampled, and the strongest one of the R, G or B is assigned as a command. 
Thus, the direction of the curve reflects the dominant color factor 
To test locally, you can download this project; 
[[Media:Turtle_homework_02_modified.zip]] 
[[Image:KK_turtle02.png|thumb|left|200px]] 
 
 

== Week 05 ==

1. [https://codepen.io/kayk5654/pen/VmWEgy recursive curve] 
[[Image:KK_fractal01.png|thumb|left|200px]] 
 

2. [https://codepen.io/kayk5654/pen/ObgBda L-system] 
[[Image:KK_fractal2.png|thumb|left|200px]] 
 
 

== Week 06 ==

[https://codepen.io/kayk5654/pen/wgaYjW breitenberg vehicle] 
Each vehicles prefer either of red, green or blue lights. 
You can drag the lights by keep pressing the central point of the light. 
[[Image:KK_breitenberg_vehicle1.png|thumb|left|200px]] 
 
 

== Week 07 ==

[https://codepen.io/kayk5654/pen/ygQGBP breitenberg vehicle with custom environment] 
Vehicles draw streaks with brushes. 
Each vehicles prefers either of dark area or bright area of their environment. 
 
[https://codepen.io/kayk5654/pen/ZLqPKX My original sketch] uses external .png file as brushes. 
You can download .zip and test it with your own brush image on your local editor. 
[[Media:Breitenberg_vehicle_homework_1.zip]] 
[[Image:KK_breitenberg_vehicle2.png|thumb|left|200px]] 
 

 

== Week 10 ==

[https://codepen.io/kayk5654/pen/vggavj magnetic matrix] 
Needles moves continuously by the influence of the noise field. 
When you drag on the needles, they create circular pattern around the mouse pointer. 
[[Image:KK_magnetrix.png|thumb|left|200px]] 
 
 

== Week 11/12 ==

[https://codepen.io/kayk5654/pen/oBBMOp soundfun] 
This sketch has 4 visualization functions. 
"drawLevel" shows the loudness of the sound. 
"drawWaveform" and "drawFFT" shows waveform and the result of FFT analysis. 
"drawOsci" shows waveforms of audio input from the mic of your computer 
Also, there are different functional sounds assigned 1 - 6 keys on your keyboard. 
[[Image:KK_soundfun.png|thumb|left|200px]] 
 
 

== Semester project ==
 
I have tried to generate curves on the surface of 3d model, so that the curvy patterns of mesh forms 3d object. 
The idea comes from Japanese traditional patterns of [http://bit.ly/2llmlqD water flow] , 
and I'd like to get smilar result by adjusting parameters of noise. 
 
Work in progress: 
[[File:KK_meandering_wip1.png|200px|thumb|left]] 
 
[[:File:curve generation test 04.zip]] 
[[File:KK_meandering_wip2.png|200px|thumb|left]] 
[[File:KK_meandering_wip3.png|200px|thumb|left]] 
 
[[:File:curve generation test 05.zip]] 
[[File:KK_meandering_wip4.png|200px|thumb|left]] 
[[File:KK_meandering_wip5.png|200px|thumb|left]] 
 
 
Reference: 
[https://threejs.org/ three.js] 
[https://github.com/spite/THREE.MeshLine THREE.Meshline]

GMU:Meandering through Space/Kei Kitamura

2017-03-14T08:08:38Z

Kei kitamura: /* Semester project */

[[User:Kei_kitamura]]
 
== Week 01 ==
[http://codepen.io/kayk5654/pen/LbjJmo Representation of the curve drawing instruction] 
The drawing instruction is [[File:Drawaline.pdf|here]]
[[Image:KK_firstcurve.png|thumb|left|200px]] 
 
 

== Week 03 ==

1. [https://codepen.io/kayk5654/pen/eBpKyY random distribution function] 
[[Image:KK_randomness.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/ZBbRXz curve controlled by randomness] 
[[Image:KK_randomwalk.png|thumb|left|200px]] 
 
 
== Week 04 ==

1. [https://codepen.io/kayk5654/pen/woMQZv turtle walk] 
The curve shows the turning point of the turtle. 
[[Image:KK_turtle01.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/mOVQgo turtle walk with data] 
The selected background image is converted to the command which defines the direction of turtle walk. 
Each pixels of the image are sampled, and the strongest one of the R, G or B is assigned as a command. 
Thus, the direction of the curve reflects the dominant color factor 
To test locally, you can download this project; 
[[Media:Turtle_homework_02_modified.zip]] 
[[Image:KK_turtle02.png|thumb|left|200px]] 
 
 

== Week 05 ==

1. [https://codepen.io/kayk5654/pen/VmWEgy recursive curve] 
[[Image:KK_fractal01.png|thumb|left|200px]] 
 

2. [https://codepen.io/kayk5654/pen/ObgBda L-system] 
[[Image:KK_fractal2.png|thumb|left|200px]] 
 
 

== Week 06 ==

[https://codepen.io/kayk5654/pen/wgaYjW breitenberg vehicle] 
Each vehicles prefer either of red, green or blue lights. 
You can drag the lights by keep pressing the central point of the light. 
[[Image:KK_breitenberg_vehicle1.png|thumb|left|200px]] 
 
 

== Week 07 ==

[https://codepen.io/kayk5654/pen/ygQGBP breitenberg vehicle with custom environment] 
Vehicles draw streaks with brushes. 
Each vehicles prefers either of dark area or bright area of their environment. 
 
[https://codepen.io/kayk5654/pen/ZLqPKX My original sketch] uses external .png file as brushes. 
You can download .zip and test it with your own brush image on your local editor. 
[[Media:Breitenberg_vehicle_homework_1.zip]] 
[[Image:KK_breitenberg_vehicle2.png|thumb|left|200px]] 
 

 

== Week 10 ==

[https://codepen.io/kayk5654/pen/vggavj magnetic matrix] 
Needles moves continuously by the influence of the noise field. 
When you drag on the needles, they create circular pattern around the mouse pointer. 
[[Image:KK_magnetrix.png|thumb|left|200px]] 
 
 

== Week 11/12 ==

[https://codepen.io/kayk5654/pen/oBBMOp soundfun] 
This sketch has 4 visualization functions. 
"drawLevel" shows the loudness of the sound. 
"drawWaveform" and "drawFFT" shows waveform and the result of FFT analysis. 
"drawOsci" shows waveforms of audio input from the mic of your computer 
Also, there are different functional sounds assigned 1 - 6 keys on your keyboard. 
[[Image:KK_soundfun.png|thumb|left|200px]] 
 
 

== Semester project ==
 
I have tried to generate curves on the surface of 3d model, so that the curvy patterns of mesh forms 3d object. 
The idea comes from Japanese traditional patterns of [http://bit.ly/2llmlqD water flow] , 
and I'd like to get smilar result by adjusting parameters of noise. 
 
Work in progress: 
[[File:KK_meandering_wip1.png|200px|thumb|left]] 
[[:File:curve generation test 04.zip]] 
[[File:KK_meandering_wip2.png|200px|thumb|left]] 
[[File:KK_meandering_wip3.png|200px|thumb|left]] 
[[:File:curve generation test 05.zip]] 
[[File:KK_meandering_wip4.png|200px|thumb|left]] 
[[File:KK_meandering_wip5.png|200px|thumb|left]] 
 
 
Reference: 
[https://threejs.org/ three.js] 
[https://github.com/spite/THREE.MeshLine THREE.Meshline]

File:Curve generation test 05.zip

2017-03-14T08:08:21Z

Kei kitamura: File uploaded with MsUpload

File uploaded with MsUpload

File:Curve generation test 04.zip

2017-03-14T08:08:13Z

Kei kitamura: File uploaded with MsUpload

File uploaded with MsUpload

GMU:Meandering through Space/Kei Kitamura

2017-03-12T12:05:29Z

Kei kitamura: /* Semester project */

[[User:Kei_kitamura]]
 
== Week 01 ==
[http://codepen.io/kayk5654/pen/LbjJmo Representation of the curve drawing instruction] 
The drawing instruction is [[File:Drawaline.pdf|here]]
[[Image:KK_firstcurve.png|thumb|left|200px]] 
 
 

== Week 03 ==

1. [https://codepen.io/kayk5654/pen/eBpKyY random distribution function] 
[[Image:KK_randomness.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/ZBbRXz curve controlled by randomness] 
[[Image:KK_randomwalk.png|thumb|left|200px]] 
 
 
== Week 04 ==

1. [https://codepen.io/kayk5654/pen/woMQZv turtle walk] 
The curve shows the turning point of the turtle. 
[[Image:KK_turtle01.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/mOVQgo turtle walk with data] 
The selected background image is converted to the command which defines the direction of turtle walk. 
Each pixels of the image are sampled, and the strongest one of the R, G or B is assigned as a command. 
Thus, the direction of the curve reflects the dominant color factor 
To test locally, you can download this project; 
[[Media:Turtle_homework_02_modified.zip]] 
[[Image:KK_turtle02.png|thumb|left|200px]] 
 
 

== Week 05 ==

1. [https://codepen.io/kayk5654/pen/VmWEgy recursive curve] 
[[Image:KK_fractal01.png|thumb|left|200px]] 
 

2. [https://codepen.io/kayk5654/pen/ObgBda L-system] 
[[Image:KK_fractal2.png|thumb|left|200px]] 
 
 

== Week 06 ==

[https://codepen.io/kayk5654/pen/wgaYjW breitenberg vehicle] 
Each vehicles prefer either of red, green or blue lights. 
You can drag the lights by keep pressing the central point of the light. 
[[Image:KK_breitenberg_vehicle1.png|thumb|left|200px]] 
 
 

== Week 07 ==

[https://codepen.io/kayk5654/pen/ygQGBP breitenberg vehicle with custom environment] 
Vehicles draw streaks with brushes. 
Each vehicles prefers either of dark area or bright area of their environment. 
 
[https://codepen.io/kayk5654/pen/ZLqPKX My original sketch] uses external .png file as brushes. 
You can download .zip and test it with your own brush image on your local editor. 
[[Media:Breitenberg_vehicle_homework_1.zip]] 
[[Image:KK_breitenberg_vehicle2.png|thumb|left|200px]] 
 

 

== Week 10 ==

[https://codepen.io/kayk5654/pen/vggavj magnetic matrix] 
Needles moves continuously by the influence of the noise field. 
When you drag on the needles, they create circular pattern around the mouse pointer. 
[[Image:KK_magnetrix.png|thumb|left|200px]] 
 
 

== Week 11/12 ==

[https://codepen.io/kayk5654/pen/oBBMOp soundfun] 
This sketch has 4 visualization functions. 
"drawLevel" shows the loudness of the sound. 
"drawWaveform" and "drawFFT" shows waveform and the result of FFT analysis. 
"drawOsci" shows waveforms of audio input from the mic of your computer 
Also, there are different functional sounds assigned 1 - 6 keys on your keyboard. 
[[Image:KK_soundfun.png|thumb|left|200px]] 
 
 

== Semester project ==
 
I have tried to generate curves on the surface of 3d model, so that the curvy patterns of mesh forms 3d object. 
The idea comes from Japanese traditional patterns of [http://bit.ly/2llmlqD water flow] , 
and I'd like to get smilar result by adjusting parameters of noise. 
 
Work in progress: 
[[File:KK_meandering_wip1.png|200px|thumb|left]] 
[[File:KK_meandering_wip2.png|200px|thumb|left]] 
[[File:KK_meandering_wip3.png|200px|thumb|left]] 
[[File:KK_meandering_wip4.png|200px|thumb|left]] 
[[File:KK_meandering_wip5.png|200px|thumb|left]] 
 
 
Reference: 
[https://threejs.org/ three.js] 
[https://github.com/spite/THREE.MeshLine THREE.Meshline]

File:KK meandering wip5.png

2017-03-12T12:05:08Z

Kei kitamura: File uploaded with MsUpload

File uploaded with MsUpload

File:KK meandering wip4.png

2017-03-12T12:05:07Z

Kei kitamura: File uploaded with MsUpload

File uploaded with MsUpload

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-10T16:04:32Z

Kei kitamura: /* Methods */

== Concept==

This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external multiple 2D coordinates. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look by texture visual effects. 
 
 

==File==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch. 
 
 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
 
 

==Result==
[[File: KK_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_offset.png|200px|thumb|left]] 
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-10T16:04:04Z

Kei kitamura: /* Methods */

== Concept==

This is an experiment to change the texture of videos. 
A video of audience, which comes from internal webcam of the computer, is transformed by external multiple 2D coordinates. 
The aim of this experiment is to represent a different impression while people see what they usually see in their life, by changing textures. 
It is the first step of giving different look by texture visual effects. 
 
 

==File==
The max patch can be downloaded from here; 
[[Media:Pixel_sampling_test_02.maxpat]] 
 
Also, here is the patch I used for osc communication with other patches 
[[Media:OSC_Network.maxpat]]
 
 

==Methods==
1. Capture a video from the webcam 
[[File: KK_dataflow_step1.png|200px|thumb|left]] 
Using jit.brab object, the video from a webcam can be captured and integrated with other max objects. 
The captured video is sent to jit.matrix object. 
In the sample patch, a large toggle button in the center of the window activates this step. 
 
2.Generate noise maps for masking 
[[File: KK_dataflow_step2.png|200px|thumb|left]] 
Next to the video capture part, there are some objects to generate a monochrome nonise texture. 
jit.bfg object generates actual noise, and it enables to select several types of noise. 
In this patch, a simplex noise is used, but there is another noise mask using curl noise in this patch. 
 
[[File: KK_dataflow_step3.png|200px|thumb|left]] 
 
 

==Result==
[[File: KK_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_chromakey.png|200px|thumb|left]] 
[[File: KK_dataflow_offset.png|200px|thumb|left]] 
[[File: KK_dataflow_overview.png|200px|thumb|left]] 
[[File: KK_dataflow_result.png|200px|thumb|left]]

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-10T15:55:17Z

Kei kitamura: /* Methods */

File:KK dataflow step3.png

2017-03-10T15:54:57Z

Kei kitamura: File uploaded with MsUpload

File uploaded with MsUpload

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-10T15:52:15Z

Kei kitamura:

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-10T15:51:22Z

Kei kitamura:

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-10T15:50:50Z

Kei kitamura:

File:KK dataflow step2.png

2017-03-10T15:50:37Z

Kei kitamura:

== Summary ==

== Copyright status: ==

== Source: ==

File:KK dataflow step1.png

2017-03-10T15:49:12Z

Kei kitamura:

== Summary ==

== Copyright status: ==

== Source: ==

GMU:Dataflow/Jam session/Kei Kitamura

2017-03-10T15:25:14Z

Kei kitamura:

File:OSC Network.maxpat

2017-03-10T15:24:17Z

Kei kitamura:

== Summary ==

== Copyright status: ==

== Source: ==

File:Pixel sampling test 02.maxpat

2017-03-10T15:22:13Z

Kei kitamura:

== Summary ==

== Copyright status: ==

== Source: ==

GMU:Meandering through Space/Kei Kitamura

2017-03-01T11:09:50Z

Kei kitamura: /* Semester project */

[[User:Kei_kitamura]]
 
== Week 01 ==
[http://codepen.io/kayk5654/pen/LbjJmo Representation of the curve drawing instruction] 
The drawing instruction is [[File:Drawaline.pdf|here]]
[[Image:KK_firstcurve.png|thumb|left|200px]] 
 
 

== Week 03 ==

1. [https://codepen.io/kayk5654/pen/eBpKyY random distribution function] 
[[Image:KK_randomness.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/ZBbRXz curve controlled by randomness] 
[[Image:KK_randomwalk.png|thumb|left|200px]] 
 
 
== Week 04 ==

1. [https://codepen.io/kayk5654/pen/woMQZv turtle walk] 
The curve shows the turning point of the turtle. 
[[Image:KK_turtle01.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/mOVQgo turtle walk with data] 
The selected background image is converted to the command which defines the direction of turtle walk. 
Each pixels of the image are sampled, and the strongest one of the R, G or B is assigned as a command. 
Thus, the direction of the curve reflects the dominant color factor 
To test locally, you can download this project; 
[[Media:Turtle_homework_02_modified.zip]] 
[[Image:KK_turtle02.png|thumb|left|200px]] 
 
 

== Week 05 ==

1. [https://codepen.io/kayk5654/pen/VmWEgy recursive curve] 
[[Image:KK_fractal01.png|thumb|left|200px]] 
 

2. [https://codepen.io/kayk5654/pen/ObgBda L-system] 
[[Image:KK_fractal2.png|thumb|left|200px]] 
 
 

== Week 06 ==

[https://codepen.io/kayk5654/pen/wgaYjW breitenberg vehicle] 
Each vehicles prefer either of red, green or blue lights. 
You can drag the lights by keep pressing the central point of the light. 
[[Image:KK_breitenberg_vehicle1.png|thumb|left|200px]] 
 
 

== Week 07 ==

[https://codepen.io/kayk5654/pen/ygQGBP breitenberg vehicle with custom environment] 
Vehicles draw streaks with brushes. 
Each vehicles prefers either of dark area or bright area of their environment. 
 
[https://codepen.io/kayk5654/pen/ZLqPKX My original sketch] uses external .png file as brushes. 
You can download .zip and test it with your own brush image on your local editor. 
[[Media:Breitenberg_vehicle_homework_1.zip]] 
[[Image:KK_breitenberg_vehicle2.png|thumb|left|200px]] 
 

 

== Week 10 ==

[https://codepen.io/kayk5654/pen/vggavj magnetic matrix] 
Needles moves continuously by the influence of the noise field. 
When you drag on the needles, they create circular pattern around the mouse pointer. 
[[Image:KK_magnetrix.png|thumb|left|200px]] 
 
 

== Week 11/12 ==

[https://codepen.io/kayk5654/pen/oBBMOp soundfun] 
This sketch has 4 visualization functions. 
"drawLevel" shows the loudness of the sound. 
"drawWaveform" and "drawFFT" shows waveform and the result of FFT analysis. 
"drawOsci" shows waveforms of audio input from the mic of your computer 
Also, there are different functional sounds assigned 1 - 6 keys on your keyboard. 
[[Image:KK_soundfun.png|thumb|left|200px]] 
 
 

== Semester project ==
 
I have tried to generate curves on the surface of 3d model, so that the curvy patterns of mesh forms 3d object. 
The idea comes from Japanese traditional patterns of [http://bit.ly/2llmlqD water flow] , 
and I'd like to get smilar result by adjusting parameters of noise. 
 
Work in progress: 
[[File:KK_meandering_wip1.png|200px|thumb|left]] 
[[File:KK_meandering_wip2.png|200px|thumb|left]] 
[[File:KK_meandering_wip3.png|200px|thumb|left]] 
 
 
Reference: 
[https://threejs.org/ three.js] 
[https://github.com/spite/THREE.MeshLine THREE.Meshline]

GMU:Meandering through Space/Kei Kitamura

2017-03-01T11:07:14Z

Kei kitamura: /* Semester project */

[[User:Kei_kitamura]]
 
== Week 01 ==
[http://codepen.io/kayk5654/pen/LbjJmo Representation of the curve drawing instruction] 
The drawing instruction is [[File:Drawaline.pdf|here]]
[[Image:KK_firstcurve.png|thumb|left|200px]] 
 
 

== Week 03 ==

1. [https://codepen.io/kayk5654/pen/eBpKyY random distribution function] 
[[Image:KK_randomness.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/ZBbRXz curve controlled by randomness] 
[[Image:KK_randomwalk.png|thumb|left|200px]] 
 
 
== Week 04 ==

1. [https://codepen.io/kayk5654/pen/woMQZv turtle walk] 
The curve shows the turning point of the turtle. 
[[Image:KK_turtle01.png|thumb|left|200px]] 
 
2. [https://codepen.io/kayk5654/pen/mOVQgo turtle walk with data] 
The selected background image is converted to the command which defines the direction of turtle walk. 
Each pixels of the image are sampled, and the strongest one of the R, G or B is assigned as a command. 
Thus, the direction of the curve reflects the dominant color factor 
To test locally, you can download this project; 
[[Media:Turtle_homework_02_modified.zip]] 
[[Image:KK_turtle02.png|thumb|left|200px]] 
 
 

== Week 05 ==

1. [https://codepen.io/kayk5654/pen/VmWEgy recursive curve] 
[[Image:KK_fractal01.png|thumb|left|200px]] 
 

2. [https://codepen.io/kayk5654/pen/ObgBda L-system] 
[[Image:KK_fractal2.png|thumb|left|200px]] 
 
 

== Week 06 ==

[https://codepen.io/kayk5654/pen/wgaYjW breitenberg vehicle] 
Each vehicles prefer either of red, green or blue lights. 
You can drag the lights by keep pressing the central point of the light. 
[[Image:KK_breitenberg_vehicle1.png|thumb|left|200px]] 
 
 

== Week 07 ==

[https://codepen.io/kayk5654/pen/ygQGBP breitenberg vehicle with custom environment] 
Vehicles draw streaks with brushes. 
Each vehicles prefers either of dark area or bright area of their environment. 
 
[https://codepen.io/kayk5654/pen/ZLqPKX My original sketch] uses external .png file as brushes. 
You can download .zip and test it with your own brush image on your local editor. 
[[Media:Breitenberg_vehicle_homework_1.zip]] 
[[Image:KK_breitenberg_vehicle2.png|thumb|left|200px]] 
 

 

== Week 10 ==

[https://codepen.io/kayk5654/pen/vggavj magnetic matrix] 
Needles moves continuously by the influence of the noise field. 
When you drag on the needles, they create circular pattern around the mouse pointer. 
[[Image:KK_magnetrix.png|thumb|left|200px]] 
 
 

== Week 11/12 ==

[https://codepen.io/kayk5654/pen/oBBMOp soundfun] 
This sketch has 4 visualization functions. 
"drawLevel" shows the loudness of the sound. 
"drawWaveform" and "drawFFT" shows waveform and the result of FFT analysis. 
"drawOsci" shows waveforms of audio input from the mic of your computer 
Also, there are different functional sounds assigned 1 - 6 keys on your keyboard. 
[[Image:KK_soundfun.png|thumb|left|200px]] 
 
 

== Semester project ==
 
I have tried to generate curves on the surface of 3d model, so that the curvy patterns of mesh forms 3d object. 
The idea comes from Japanese traditional patterns of [http://bit.ly/2llmlqD |water flow] , 
and I'd like to get smilar result by adjusting parameters of noise. 
 
Work in progress: 
[[File:KK_meandering_wip1.png|200px|thumb|left]] 
[[File:KK_meandering_wip2.png|200px|thumb|left]] 
[[File:KK_meandering_wip3.png|200px|thumb|left]] 
 
 
Reference: 
[https://threejs.org/ three.js] 
[https://github.com/spite/THREE.MeshLine THREE.Meshline]