A Pixel Dissimilarity Measure That Is Insensitive to Image Sampling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Stereo Matching Using Belief Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparison of Graph Cuts with Belief Propagation for Stereo, using Identical MRF Parameters
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Convergent Tree-Reweighted Message Passing for Energy Minimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of Stereo Matching Costs on Images with Radiometric Differences
IEEE Transactions on Pattern Analysis and Machine Intelligence
VLSI architecture for MRF based stereo matching
SAMOS'07 Proceedings of the 7th international conference on Embedded computer systems: architectures, modeling, and simulation
Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
High-Performance Heterogeneous Computing with the Convey HC-1
Computing in Science and Engineering
MAP estimation via agreement on trees: message-passing and linear programming
IEEE Transactions on Information Theory
Hardware-Efficient Belief Propagation
IEEE Transactions on Circuits and Systems for Video Technology
Multi-hypothesis motion planning for visual object tracking
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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We demonstrate a video-rate stereo matching system implemented on a hybrid CPU+FPGA platform (Convey HC-1). Emerging applications such as 3D gesture recognition and automotive navigation demand fast and high quality stereo vision. We describe a custom hardware-accelerated Markov Random Field inference system for this task. Starting from a core architecture for streaming tree-reweighted message passing (TRW-S) inference, we describe the end-to-end system engineering needed to move from this single frame message update to full stereo video. We partition the stereo matching procedure across the CPU and the FPGAs, and apply both function-level pipelining and frame-level parallelism to achieve the required speed. Experimental results show that our system achieves a speed of 12 frames per second for challenging video stereo matching tasks. We note that this appears to be the first implementation of TRW-S inference at video rates, and that our system is also significantly faster than several recent GPU implementations of similar stereo inference methods based on belief propagation (BP).