{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T13:38:48Z","timestamp":1758893928878,"version":"3.37.3"},"reference-count":16,"publisher":"World Scientific Pub Co Pte Ltd","issue":"06","funder":[{"DOI":"10.13039\/501100003819","name":"Natural Science Foundation of Hubei Province","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2018,6]]},"abstract":"<jats:p> Belief propagation (BP) algorithm still exists some shortages, such as inaccurate edge preservation and ambiguous detail information in the foreground, while self-adapting dissimilarity measure (SDM) also exists some shortages, such as ill textureless and occluded information in the background. To address these problems, we present a novel stereo matching algorithm fusing BP and SDM with an excellent background and foreground information. Lots of experiments show that BP and SDM can complement each other. BP algorithm can hold the better background information due to message propagation inference, whereas SDM can possess the better foreground information due to detail treatment. Therefore, a piecewise function is proposed, which can combine BP algorithm in an excellent background information and SDM in the foreground information, and greatly improve the disparity effect as a whole. We also expect that this work can attract more attention on combination of local methods and global methods, due to its simplicity, efficiency, and accuracy. Experimental results show that the proposed method can keep the superior performance and hold better background and foreground on the Middlebury datasets, compared to BP and SDM. <\/jats:p>","DOI":"10.1142\/s0218001418500192","type":"journal-article","created":{"date-parts":[[2017,11,28]],"date-time":"2017-11-28T03:27:58Z","timestamp":1511839678000},"page":"1850019","source":"Crossref","is-referenced-by-count":5,"title":["A Combined Back and Foreground-Based Stereo Matching Algorithm Using Belief Propagation and Self-Adapting Dissimilarity Measure"],"prefix":"10.1142","volume":"32","author":[{"given":"Xiaofeng","family":"Wang","sequence":"first","affiliation":[{"name":"College of Mathematical and Physical Sciences, Chongqing University of Science and Technology, Chongqing 401331, P. R. China"}]},{"given":"Yingying","family":"Su","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Chongqing University of Science and Technology, Chongqing 401331, P. R. China"}]},{"given":"Liming","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Science, Hubei University for Nationalities, Enshi 445000, P. R. China"}]},{"given":"Jie","family":"Tan","sequence":"additional","affiliation":[{"name":"College of Mathematical and Physical Sciences, Chongqing University of Science and Technology, Chongqing 401331, P. R. 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