{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T07:10:20Z","timestamp":1763968220330,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2016,12,21]],"date-time":"2016-12-21T00:00:00Z","timestamp":1482278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11547157","61100004"],"award-info":[{"award-number":["11547157","61100004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Heilongjiang Province of China","award":["F201320"],"award-info":[{"award-number":["F201320"]}]},{"name":"Harbin Municipal Science and Technology Bureau","award":["2014RFQXJ073"],"award-info":[{"award-number":["2014RFQXJ073"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>This paper presents a segmentation-based stereo matching algorithm using an adaptive multi-cost approach, which is exploited for obtaining accuracy disparity maps. The main contribution is to integrate the appealing properties of multi-cost approach into the segmentation-based framework. Firstly, the reference image is segmented by using the mean-shift algorithm. Secondly, the initial disparity of each segment is estimated by an adaptive multi-cost method, which consists of a novel multi-cost function and an adaptive support window cost aggregation strategy. The multi-cost function increases the robustness of the initial raw matching costs calculation and the adaptive window reduces the matching ambiguity effectively. Thirdly, an iterative outlier suppression and disparity plane parameters fitting algorithm is designed to estimate the disparity plane parameters. Lastly, an energy function is formulated in segment domain, and the optimal plane label is approximated by belief propagation. The experimental results with the Middlebury stereo datasets, along with synthesized and real-world stereo images, demonstrate the effectiveness of the proposed approach.<\/jats:p>","DOI":"10.3390\/sym8120159","type":"journal-article","created":{"date-parts":[[2016,12,23]],"date-time":"2016-12-23T04:09:09Z","timestamp":1482466149000},"page":"159","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Accurate Dense Stereo Matching Based on Image Segmentation Using an Adaptive Multi-Cost Approach"],"prefix":"10.3390","volume":"8","author":[{"given":"Ning","family":"Ma","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, Nantong Street 145, Harbin 150001, China"},{"name":"College of Computer Science and Information Engineering, Harbin Normal University, Normal University Road 1, Harbin 150001, China"}]},{"given":"Yubo","family":"Men","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, Nantong Street 145, Harbin 150001, China"}]},{"given":"Chaoguang","family":"Men","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, Nantong Street 145, Harbin 150001, China"}]},{"given":"Xiang","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, Nantong Street 145, Harbin 150001, China"}]}],"member":"1968","published-online":{"date-parts":[[2016,12,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1023\/A:1014573219977","article-title":"A taxonomy and evaluation of dense two-frame stereo correspondence algorithms","volume":"47","author":"Scharstein","year":"2002","journal-title":"Int. J. Comput. Vis."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1109\/TCSVT.2012.2223794","article-title":"Domain transformation-based efficient cost aggregation for local stereo matching","volume":"23","author":"Pham","year":"2013","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.jvcir.2011.02.001","article-title":"Obtaining depth map from segment-based stereo matching using graph cuts","volume":"22","author":"Wang","year":"2011","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Scharstein, D., and Pal, C. (2007, January 17\u201322). Learning conditional random fields for stereo. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, USA.","DOI":"10.1109\/CVPR.2007.383191"},{"key":"ref_5","unstructured":"Scharstein, D., and Szeliski, R. (2003, January 18\u201320). High-accuracy stereo depth maps using structured light. Proceedings of the Computer Vision and Pattern Recognition, Madison, WI, USA."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1145\/2584659","article-title":"Hardware acceleration for an accurate stereo vision system using mini-census adaptive support region","volume":"13","author":"Shan","year":"2014","journal-title":"ACM Trans. Embed. Comput. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.isprsjprs.2014.02.006","article-title":"On accurate dense stereo-matching using a local adaptive multi-cost approach","volume":"91","author":"Stentoumis","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.patrec.2013.11.009","article-title":"A robust cost function for stereo matching of road scenes","volume":"38","author":"Miron","year":"2014","journal-title":"Pattern Recognit. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.cviu.2015.02.005","article-title":"Adaptive stereo similarity fusion using confidence measures","volume":"135","author":"Saygili","year":"2015","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Stentoumis, C., Grammatikopoulos, L., Kalisperakis, I., Karras, G., and Petsa, E. (2015, January 21). Stereo matching based on census transformation of image gradients. Proceedings of the SPIE Optical Metrology, International Society for Optics and Photonics, Munich, Germany.","DOI":"10.1117\/12.2184763"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Klaus, A., Sormann, M., and Karner, K. (2006, January 20\u201324). Segment-based stereo matching using belief propagation and a self-adapting dissimilarity measure. Proceedings of the IEEE 18th International Conference on Pattern Recognition (ICPR\u201906), Hong Kong, China.","DOI":"10.1109\/ICPR.2006.1033"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.imavis.2014.12.001","article-title":"Enhanced disparity estimation in stereo images","volume":"35","author":"Kordelas","year":"2015","journal-title":"Image Vis. Comput."},{"key":"ref_13","unstructured":"Wang, Z.F., and Zheng, Z.G. (2008, January 23\u201328). A region based stereo matching algorithm using cooperative optimization. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, AK, USA."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2182","DOI":"10.1109\/TIP.2015.2416654","article-title":"PM-PM: PatchMatch with Potts model for object segmentation and stereo matching","volume":"24","author":"Xu","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Taguchi, Y., Wilburn, B., and Zitnick, C.L. (2008, January 23\u201328). Stereo reconstruction with mixed pixels using adaptive over-segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, AK, USA.","DOI":"10.1109\/CVPR.2008.4587691"},{"key":"ref_16","first-page":"163285","article-title":"Local stereo matching using adaptive local segmentation","volume":"2012","author":"Spreeuwers","year":"2012","journal-title":"ISRN Mach. Vis."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"650","DOI":"10.1109\/TPAMI.2006.70","article-title":"Adaptive support-weight approach for correspondence search","volume":"28","author":"Yoon","year":"2006","journal-title":"IEEE Trans. Pattern Anal."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1109\/TCSVT.2009.2020478","article-title":"Cross-based local stereo matching using orthogonal integral images","volume":"19","author":"Zhang","year":"2009","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_19","unstructured":"Veksler, O. (2003, January 18\u201320). Fast variable window for stereo correspondence using integral images. Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Madison, WI, USA."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1023\/A:1014510328154","article-title":"A simple stereo algorithm to recover precise object boundaries and smooth surfaces","volume":"47","author":"Okutomi","year":"2002","journal-title":"Int. J. Comput. Vis."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1109\/TPAMI.2012.156","article-title":"Fast cost-volume filtering for visual correspondence and beyond","volume":"35","author":"Hosni","year":"2013","journal-title":"IEEE Trans. Pattern Anal."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"027201","DOI":"10.1117\/1.OE.52.2.027201","article-title":"Stereo matching algorithm based on illumination normal similarity and adaptive support weight","volume":"52","author":"Gao","year":"2013","journal-title":"Opt. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1007\/s11554-012-0275-4","article-title":"Real-time stereo using approximated joint bilateral filtering and dynamic programming","volume":"9","author":"Wang","year":"2014","journal-title":"J. Real-Time Image Process."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Taniai, T., Matsushita, Y., and Naemura, T. (2014, January 23\u201328). Graph cut based continuous stereo matching using locally shared labels. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA.","DOI":"10.1109\/CVPR.2014.209"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1007\/s11263-013-0653-9","article-title":"Pmbp: Patchmatch belief propagation for correspondence field estimation","volume":"110","author":"Besse","year":"2014","journal-title":"Int. J. Comput. Vis."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1109\/TPAMI.2007.1166","article-title":"Stereo Processing by Semiglobal Matching and Mutual Information","volume":"30","author":"Hirschmuller","year":"2008","journal-title":"IEEE Trans. Pattern Anal."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1109\/34.1000236","article-title":"Mean shift: A robust approach toward feature space analysis","volume":"24","author":"Comaniciu","year":"2002","journal-title":"IEEE Trans. Pattern Anal."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1631\/jzus.C1100311","article-title":"Accurate real-time stereo correspondence using intra-and inter-scanline optimization","volume":"13","author":"Yao","year":"2012","journal-title":"J. Zhejiang Univ. Sci. C"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Scharstein, D., Hirschm\u00fcller, H., Kitajima, Y., Krathwohl, G., Ne\u0161i\u0107, N., Wang, X., and Westling, P. (2014, January 2\u20135). High-resolution stereo datasets with subpixel-accurate ground truth. Proceedings of the German Conference on Pattern Recognition, M\u00fcnster, Germany.","DOI":"10.1007\/978-3-319-11752-2_3"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Hirschmuller, H., and Scharstein, D. (2007, January 17\u201322). Evaluation of cost functions for stereo matching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, USA.","DOI":"10.1109\/CVPR.2007.383248"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Richardt, C., Orr, D., Davies, I., Criminisi, A., and Dodgson, N.A. (2010, January 5\u201311). Real-time spatiotemporal stereo matching using the dual-cross-bilateral grid. Proceedings of the European Conference on Computer Vision, Crete, Greece.","DOI":"10.1007\/978-3-642-15558-1_37"},{"key":"ref_32","unstructured":"Park, M.G., and Yoon, K.J. (2016). As-planar-as-possible depth map estimation. IEEE Trans. Pattern Anal., submitted."},{"key":"ref_33","unstructured":"Li, L., Zhang, S., Yu, X., and Zhang, L. (2016). PMSC: PatchMatch-based superpixel cut for accurate stereo matching. IEEE T. Circ. Syst. Vid."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Zhang, C., Li, Z., Cheng, Y., Cai, R., Chao, H., and Rui, Y. (2015, January 13\u201316). Meshstereo: A global stereo model with mesh alignment regularization for view interpolation. Proceedings of the IEEE International Conference on Computer Vision, Santiago, Chile.","DOI":"10.1109\/ICCV.2015.238"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Kim, K.R., and Kim, C.S. (2016, January 25\u201328). Adaptive smoothness constraints for efficient stereo matching using texture and edge information. Proceedings of the Image Processing (ICIP), Phoenix, AZ, USA.","DOI":"10.1109\/ICIP.2016.7532996"},{"key":"ref_36","first-page":"1","article-title":"Stereo matching by training a convolutional neural network to compare image patches","volume":"17","author":"Zbontar","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Barron, J.T., and Poole, B. (2016, January 11\u201314). The Fast Bilateral Solver. Proceedings of the European Conference on Computer Vision, Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46487-9_38"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1109\/TIP.2015.2395820","article-title":"Accurate stereo matching by two-step energy minimization","volume":"24","author":"Mozerov","year":"2015","journal-title":"IEEE Trans. Image Process."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/8\/12\/159\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:28:58Z","timestamp":1760210938000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/8\/12\/159"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12,21]]},"references-count":38,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2016,12]]}},"alternative-id":["sym8120159"],"URL":"https:\/\/doi.org\/10.3390\/sym8120159","relation":{},"ISSN":["2073-8994"],"issn-type":[{"type":"electronic","value":"2073-8994"}],"subject":[],"published":{"date-parts":[[2016,12,21]]}}}