From 2-D pictures to 3 dimensions

UC-San Diego computer scientists win award for algorithms for 3-D reconstructions from 2-D images

Your pictures of the Grand Canyon, Times Square or other destinations may be pretty good, but wouldn't it be nice to show them off in three dimensions? An award-winning 3-D... Click here for more information.

Your pictures of the Grand Canyon, Times Square or other destinations may be pretty good, but wouldn’t it be nice to show them off in three dimensions?

An award-winning 3D reconstruction algorithm designed by a team of computer science researchers from UC San Diego brings this dream within the grasp of reality.

This research gets at the heart of “autocalibration,” a well-studied, fundamental problem in computer vision. Autocalibration aims to recover the three dimensional structure of a scene using only its images, acquired from cameras whose internal settings and spatial orientations are unknown.

Autocalibraton is part of a larger 3D image reconstruction challenge that has caught the attention of Google, Microsoft and others.

Manmohan Chandraker, a fifth-year PhD student in the Department of Computer Science and Engineering at UCSD’s Jacobs School of Engineering led the work. He, Sameer Agarwal – a computer science UCSD alumnus now at the University of Washington, and their respective Ph.D. advisors, David Kriegman and Serge Belongie presented their research at the International Conference on Computer Vision (ICCV), held in Rio de Janeiro, Brazil in October 2007. ICCV is the premier conference in the field of computer vision. For this work, Chandraker took home one of three honorable mentions for ICCV’s prestigious David Marr prize.