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Cooperative Stereo Vision
This project is no longer active.
Head: Takeo Kanade
Contact: Charles Zitnick
Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213
Associated center: VASC
For more information, see this project's homepage.
We are developing a cooperative stereo vision algorithm for obtaining disparity maps and explicitly detecting occlusions. To produce smooth and detailed disparity maps, we utilize two assumptions: uniqueness and continuity. That is, the disparity maps have a unique value per pixel and are continuous almost everywhere.
Our current algorithm has been tested on several benchmark stereo image pairs. Please see our homepage for examples. We are also distributing a sample program to allow others to use our algorithm.
In the future, we hope to develop a more comprehensive package for stereo vision research. This includes creating a program for rectifying stereo image pairs and increasing the usability of our current stereo program.
Note: This list may not be comprehensive. It contains only those publications in the RI publications database. Entries are listed in reverse chronological order.