Logo and Side Nav
News
Velit dreamcatcher cardigan anim, kitsch Godard occupy art party PBR. Ex cornhole mustache cliche. Anim proident accusamus tofu. Helvetica cillum labore quis magna, try-hard chia literally street art kale chips aliquip American Apparel.
Search
Browse News Archive
- March 2014
- February 2014
- January 2014
- December 2013
- November 2013
- October 2013
- September 2013
- August 2013
- July 2013
- June 2013
- May 2013
- April 2013
- March 2013
- February 2013
- January 2013
- December 2012
- November 2012
- October 2012
- September 2012
- August 2012
- July 2012
- June 2012
- May 2012
- April 2012
- March 2012
- February 2012
- January 2012
- December 2011
- November 2011
- October 2011
- September 2011
- August 2011
- July 2011
- June 2011
- May 2011
- April 2011
- March 2011
- February 2011
- December 2010
- November 2010
- October 2010
- August 2010
- July 2010
- June 2010
- May 2010
- April 2010
- March 2010
- February 2010
- January 2010
- December 2009
- November 2009
- October 2009
- September 2009
- August 2009
- July 2009
- June 2009
- May 2009
- April 2009
- March 2009
- February 2009
- January 2009
- December 2008
- November 2008
- October 2008
- September 2008
- August 2008
- July 2008
- June 2008
- May 2008
- April 2008
- March 2008
- February 2008
- January 2008
- December 2007
- November 2007
- October 2007
- September 2007
- June 2007
- May 2007
Saturday, September 17, 2011
introducing ImagePlot visualization software: explore patterns in large image collections
DOWNLOAD IMAGEPLOT 0.9
ImagePlot creates new types of visualizations not offered by any other application. It displays your data and images as a 2D line graph or a scatter plot, with the images superimposed over data points.
Scatterplot (left) vs ImagePlot (right) of the same data. 128 paintings by Piet Mondrian created between 1905 and 1917. In each plot:
X-axis = brightness median. Y-axis = saturation median.
ImagePlot works on Mac, Windows, and Lunix.
Maximum possible visualization resolution: 2.5 GB (2,684,354,560 greyscale pixels, or 671,088,640 RGB pixels).
Largest image collection visualized so far: 1,074,790 one megabyte images.
ImagePlot was developed by the members of Software Studies Initiative with support from the National Endowment for Humanities (NEH), the California Institute for Telecommunications and Information Technology (Calit2), and the Center for Research in Computing and the Arts (CRCA)
ImagePlot team:
Lev Manovich (Professor, Visual Arts, UCSD and Director, Software Studies Initiative, Calit2)
Jeremy Douglass (Post-doctoral researcher, Calit2)
Nadia Xiangfei Zeng (ICAM undergraduate students, UCSD)
Tara Zepel (PhD student, Visual Arts, UCSD).
Along with the program, we also distribute a number of articles by Manovich, Douglass and Zepel that address methodologies for exploring large visual cultural data sets, and discuss our digital humanities projects that use ImagePlot. (The articles can be also downloaded directly from softwarestudies.com.)
Visualizations created with ImagePlot have been shown in science centers, art and design museums, and art galleries, including Graphic Design Museum (Breda, Netherlands), Gwangju Design Biennale (Korea), and The San Diego Museum of Contemporary Art.
ImagePlot software was created as part of our Cultural Analytics research program.
Share Your Image Plots:
Twitter: Use #imageplot when you tweet about your image plots.
Flickr: Use "imageplot" tag for your image plots.
Subscribe to our blog softwarestudies.com
Email us your feedback, new feature requests, bug reports.
Examples of ImagePlot visualizations: