Real-Time DSP Implementation on Local Stereo Matching

Real-time DSP stereo matching solution has been important to various applications relying on stereo vision. We proposed a 4times5 jigsaw matching template and the dual-block parallel processing technique to enhance VLIW DSP stereo matcher's performance. The 4times5 jigsaw template improves the matching quality by 1% compared with regular 4times5 block template while consuming the same amount of memory access bandwidth. Along with the benefit of the jigsaw template, the dual-block parallel processing technique, which doubles the throughput, is possible to be implemented for DSP. Together with instruction scheduling and operation pipelining, our DSP stereo matcher can achieve 50 FPS of 16 disparity levels for a 384times288 stereo image pair. Both quantitative and qualitative stereo matching results are provided at the end of this work.

[1]  Yasuhiro Kobayashi,et al.  FPGA implementation of a stereo matching processor based on window-parallel-and-pixel-parallel architecture , 2005, 48th Midwest Symposium on Circuits and Systems, 2005..

[2]  Takeo Kanade,et al.  CMU Video-Rate Stereo Machine , 1995 .

[3]  W. James MacLean,et al.  A Real-Time Large Disparity Range Stereo-System using FPGAs , 2006, Fourth IEEE International Conference on Computer Vision Systems (ICVS'06).

[4]  Peter I. Corke,et al.  Real-time stereopsis using FPGAs , 1997, FPL.

[5]  Shigeru Kimura,et al.  A convolver-based real-time stereo machine (SAZAN) , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[6]  Tomoharu Nakahara,et al.  A Multiple-baseline Stereo Method , 2002 .

[7]  Minglun Gong,et al.  Near real-time reliable stereo matching using programmable graphics hardware , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[8]  Kurt Konolige,et al.  Small Vision Systems: Hardware and Implementation , 1998 .

[9]  Philip L. Davidson,et al.  Real-time stereo vision using semi-global matching on programmable graphics hardware , 2006, SIGGRAPH '06.

[10]  Masahiro Yokomichi,et al.  Stereo Correspondence Using Color Based on Competitive-cooperative Neural Networks , 2005, Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05).

[11]  Darius Burschka,et al.  Advances in Computational Stereo , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Peter I. Corke,et al.  Quantitative Evaluation of Matching Methods and Validity Measures for Stereo Vision , 2001, Int. J. Robotics Res..

[13]  John Woodfill,et al.  Real-time stereo vision on the PARTS reconfigurable computer , 1997, Proceedings. The 5th Annual IEEE Symposium on Field-Programmable Custom Computing Machines Cat. No.97TB100186).

[14]  D. Scharstein,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001).