Architecture design of stereo matching using belief propagation

We propose a new architecture for stereo matching using belief propagation. The architecture combines our fast, fully-parallel processing element (PE) and memory-efficient tile-based BP (TBP) algorithm. On the architectural level, we develop several novel techniques, including a three stage pipeline, a message forwarding scheme, and a boundary message reuse scheme, which greatly reduce the required bandwidth and power consumption without sacrificing performance. The simulation shows that the architecture can generate HDTV720p results at 30 fps when operating at 227MHz. The high-quality depth maps enable real-time depth image based rendering and many other important applications in the 3D TV industry.

[1]  Alberto Prieto,et al.  Real-Time System for High-Image Resolution Disparity Estimation , 2007, IEEE Transactions on Image Processing.

[2]  Andrew Blake,et al.  Efficient Dense Stereo with Occlusions for New View-Synthesis by Four-State Dynamic Programming , 2006, International Journal of Computer Vision.

[3]  Daniel P. Huttenlocher,et al.  Efficient Belief Propagation for Early Vision , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[4]  Liang-Gee Chen,et al.  Fast belief propagation process element for high-quality stereo estimation , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[5]  Olga Veksler,et al.  Fast Approximate Energy Minimization via Graph Cuts , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Heiko Hirschmüller,et al.  Evaluation of Stereo Matching Costs on Images with Radiometric Differences , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Richard Szeliski,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.

[8]  Miao Liao,et al.  Real-time Global Stereo Matching Using Hierarchical Belief Propagation , 2006, BMVC.

[9]  Nanning Zheng,et al.  Stereo Matching Using Belief Propagation , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Richard Szeliski,et al.  A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Liang-Gee Chen,et al.  Analysis of belief propagation for hardware realization , 2008, 2008 IEEE Workshop on Signal Processing Systems.

[12]  Liang-Gee Chen,et al.  Hardware-Efficient Belief Propagation , 2009, IEEE Transactions on Circuits and Systems for Video Technology.