Google launch a service to perform web image search by similarity. It's a service like http://www.tineye.com/.
http://images.google.com/ A camera have appear in the text label. Drag and Drop an image on the text field or click on the camera.
A bunch of news about Computer vision, Computer Graphics, GPGPU or the mix of the three....
Showing posts with label Google. Show all posts
Showing posts with label Google. Show all posts
Thursday, June 16, 2011
Friday, July 30, 2010
Microsoft : Street Slide => Infinite Panorama
Street Slide => Browsing Street Level Imagery : (The Microsoft project page )
"Systems such as Google Street View and Bing Maps Streetside enable users to virtually visit cities by navigating between immersive 360° panoramas, or bubbles. The discrete moves from bubble to bubble enabled in these systems do not provide a good visual sense of a larger aggregate such as a whole city block. Multi-perspective "strip" panoramas can provide a visual summary of a city street but lack the full realism of immersive panoramas."
"Systems such as Google Street View and Bing Maps Streetside enable users to virtually visit cities by navigating between immersive 360° panoramas, or bubbles. The discrete moves from bubble to bubble enabled in these systems do not provide a good visual sense of a larger aggregate such as a whole city block. Multi-perspective "strip" panoramas can provide a visual summary of a city street but lack the full realism of immersive panoramas."
Libellés :
Computer Graphics,
computer vision,
Google,
Image processing
Thursday, November 19, 2009
Google Image Swirl, keywords based image clustering
Google have launch a new service. A web clustering exploration. The techno is based on keyword. All the image that share a similar keyword are linked. The interface is nice and powered by flash. But the keywords approach show rapidly is limit, the image do not share at all visual content (sometimes).
For exemple type Paris (you will find Paris hilton and Paris city photos....)
On the following experiment you see that I have typed 'Paris'. I have navigate through Paris Hilton clusters and finally I have found a architectural content... (From Paris city, Sainte Chapelle ).

So the approach is nice, but based on keywords seems to be very limited. But is allow to have a nice filtering of information.
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