A miniature stereo vision machine for real-time dense depth mapping

Authors:
Yunde Jia;Yihua Xu;Wanchun Liu;Cong Yang;Yuwen Zhu;Xiaoxun Zhang;Luping An
Affiliations:
Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing, P. R. China;Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing, P. R. China;Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing, P. R. China;Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing, P. R. China;Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing, P. R. China;Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing, P. R. China;Department of Computer Science and Engineering, Beijing Institute of Technology, Beijing, P. R. China
Venue:
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
Year:
2003

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Abstract

We have developed a miniature stereo vision machine (MSVM-2) to generate high-resolution dense depth map for application to portable intelligent robots and smart visual interface. The machine uses multiple cameras, each with a very wide field of view, to synchronously capture stereo image sequences, and then computes dense depth maps in real time. The whole algorithm, including radial distortion correction, LoG filtering, correspondence finding, and dense depth map computation, is compactly implemented in a single FPGA. The machine also has an IEEE 1394 port for video-rate data transferring to PCs and a parallel data interface port to other user-systems. The machine could achieve more than 30 frame-per-second processing rate for 640_ 480 dense depth map with a 64-pixel disparity search range and 8-bit depth precision, and up to 50 frame-per-second for a 320_ 240 depth map.