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Báo cáo hóa học: " Real-time stereo matching architecture based on 2D MRF model: a memory-efficient systolic array"
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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Real-time stereo matching architecture based on 2D MRF model: a memory-efficient systolic array | Park et al. EURASIP Journal on Image and Video Processing 2011 2011 4 http jivp.eurasipjournals.eom content 2011 1 4 D EURASIP Journal on Image and Video Processing a SpringerOpen Journal RESEARCH Open Access Real-time stereo matching architecture based on 2D MRF model a memory-efficient systolic array Sungchan Park Chao Chen Hong Jeong and Sang Hyun Han Abstract There is a growing need in computer vision applications for stereopsis requiring not only accurate distance but also fast and compact physical implementation. Global energy minimization techniques provide remarkably precise results. But they suffer from huge computational complexity. One of the main challenges is to parallelize the iterative computation solving the memory access problem between the big external memory and the massive processors. Remarkable memory saving can be obtained with our memory reduction scheme and our new architecture is a systolic array. If we expand it into N s multiple chips in a cascaded manner we can cope with various ranges of image resolutions. We have realized it using the FPGA technology. Our architecture records 19 times smaller memory than the global minimization technique which is a principal step toward real-time chip implementation of the various iterative image processing algorithms with tiny and distributed memory resources like optical flow image restoration etc. Keywords Real-time VLSI belief propagation memory resource stereo matching 1 Introduction The stereo matching problem is to find the corresponding points in a pair of images portraying the same scene. The underlying principle is that two cameras separated by a baseline capture slightly dissimilar views of the same scene. Finding the corresponding pairs is known to be the most challenging step in the binocular stereo problem. As shown in Table 1 the conventional methods can be categorized into the local and global methods 1 . The unit million disparity estimations per second MDE s is the product of the .