{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:28:06Z","timestamp":1740122886017,"version":"3.37.3"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"18","license":[{"start":{"date-parts":[[2016,9,22]],"date-time":"2016-09-22T00:00:00Z","timestamp":1474502400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Nature Science Foundation of China","award":["No.61202143"],"award-info":[{"award-number":["No.61202143"]}]},{"name":"Nature Science Foundation of China","award":["No.61572409"],"award-info":[{"award-number":["No.61572409"]}]},{"DOI":"10.13039\/501100003392","name":"Natural Science Foundation of Fujian Province","doi-asserted-by":"publisher","award":["No.2013J05100"],"award-info":[{"award-number":["No.2013J05100"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fujian Provi-nce 2011 Collaborative Innovation Center of TCM Health Management"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2017,9]]},"DOI":"10.1007\/s11042-016-3932-y","type":"journal-article","created":{"date-parts":[[2016,9,22]],"date-time":"2016-09-22T01:12:57Z","timestamp":1474506777000},"page":"18473-18488","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Detecting ground control points via convolutional neural network for stereo matching"],"prefix":"10.1007","volume":"76","author":[{"given":"Zhun","family":"Zhong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Songzhi","family":"Su","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Donglin","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaozi","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihan","family":"Lv","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,9,22]]},"reference":[{"key":"3932_CR1","unstructured":"Arandjelovi\u0107 R, Gronat P, Torii A, Pajdla T, Sivic J (2015) NetVLAD: CNN architecture for weakly supervised place recognition. arXiv: 1511.07247"},{"issue":"3","key":"3932_CR2","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1023\/A:1008150329890","volume":"33","author":"AF Bobick","year":"1999","unstructured":"Bobick AF, Intille SS (1999) Large occlusion stereo. IJCV 33(3):181\u2013200","journal-title":"IJCV"},{"issue":"11","key":"3932_CR3","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.1109\/34.969114","volume":"23","author":"Y Boykov","year":"2001","unstructured":"Boykov Y, Veksler O, Zabih R (2001) Fast approximate energy minimization via graph cuts. TPAMI 23(11):1222\u20131239","journal-title":"TPAMI"},{"key":"3932_CR4","doi-asserted-by":"crossref","unstructured":"Chen Z, Sun X, Wang L, Yu Y, Huang C (2015) A deep visual correspondence embedding model for stereo matching costs. In: ICCV, pp 972\u2013980","DOI":"10.1109\/ICCV.2015.117"},{"issue":"1","key":"3932_CR5","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1023\/A:1026501619075","volume":"40","author":"WT Freeman","year":"2000","unstructured":"Freeman WT, Pasztor EC, Carmichael OT (2000) Learning low-level vision. IJCV 40(1):25\u201347","journal-title":"IJCV"},{"key":"3932_CR6","doi-asserted-by":"crossref","unstructured":"Geiger A, Lenz P, Stiller C, Urtasun R (2013) Vision meets robotics: the kitti dataset. Int J Robot Res:0278364913491297","DOI":"10.1177\/0278364913491297"},{"key":"3932_CR7","doi-asserted-by":"crossref","unstructured":"Girshick R (2015) Fast r-cnn. In: Proceedings of the IEEE International Conference on Computer Vision (pp. 1440\u20131448)","DOI":"10.1109\/ICCV.2015.169"},{"key":"3932_CR8","doi-asserted-by":"crossref","unstructured":"Haeusler R, Nair R, Kondermann D (2013) Ensemble learning for confidence measures in stereo vision. In: CVPR. IEEE, pp 305\u2013312","DOI":"10.1109\/CVPR.2013.46"},{"key":"3932_CR9","doi-asserted-by":"crossref","unstructured":"Hermann S, Klette R (2013) Iterative semi-global matching for robust driver assistance systems. In: ACCV. Springer, pp 465\u2013478","DOI":"10.1007\/978-3-642-37431-9_36"},{"issue":"2","key":"3932_CR10","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1109\/TPAMI.2007.1166","volume":"30","author":"H Hirschm\u00fcller","year":"2008","unstructured":"Hirschm\u00fcller H (2008) Stereo processing by semiglobal matching and mutual information. TPAMI 30(2):328\u2013341","journal-title":"TPAMI"},{"key":"3932_CR11","doi-asserted-by":"crossref","unstructured":"Jia Y, Shelhamer E, Donahue J, Karayev S, Long J, Girshick R, Guadarrama S, Darrell T (2014) Caffe: convolutional architecture for fast feature embedding. In: Proceedings of the 22nd ACM international conference on multimedia. ACM, pp 675\u2013678","DOI":"10.1145\/2647868.2654889"},{"key":"3932_CR12","doi-asserted-by":"crossref","unstructured":"Kong D, Tao H (2004) A method for learning matching errors for stereo computation. In: BMVC, vol 1, p 2","DOI":"10.5244\/C.18.11"},{"key":"3932_CR13","doi-asserted-by":"crossref","unstructured":"Kong D, Tao H (2006) Stereo matching via learning multiple experts behaviors. In: BMVC, vol 1, p 2","DOI":"10.5244\/C.20.11"},{"issue":"9","key":"3932_CR14","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1109\/34.310682","volume":"16","author":"MS Lew","year":"1994","unstructured":"Lew MS, Huang TS, Wong K (1994) Learning and feature selection in stereo matching. TPAMI 16(9):869\u2013881","journal-title":"TPAMI"},{"key":"3932_CR15","unstructured":"Li W, Chen Y, Lee J, Ren G, Cosker D (2016) Blur robust optical flow using motion channel. arXiv: 1603.02253"},{"key":"3932_CR16","doi-asserted-by":"crossref","unstructured":"Li W, Cosker D (2016) Video interpolation using optical flow and laplacian smoothness. Neurocomputing","DOI":"10.1016\/j.neucom.2016.04.064"},{"key":"3932_CR17","doi-asserted-by":"crossref","unstructured":"Li W, Cosker D, Brown M, Tang R (2013) Optical flow estimation using laplacian mesh energy. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2435\u20132442","DOI":"10.1109\/CVPR.2013.315"},{"issue":"1","key":"3932_CR18","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1109\/LRA.2016.2592513","volume":"2","author":"W Li","year":"2016","unstructured":"Li W, Cosker D, Zhihan L, Brown M (2016) Nonrigid optical flow ground truth for real-world scenes with time-varying shading effects. IEEE robotics and automation letters 2(11):231\u2013238","journal-title":"IEEE Robotics and Automation Letters"},{"key":"3932_CR19","unstructured":"Liang Z, Zhi B, Yifan S, Jingdong W, Shengjin W, Chi S, Qi T (2016) Mars: a video benchmark for large-scale person re-identification. In: European conference on computer vision. Springer"},{"key":"3932_CR20","unstructured":"Motten A, Claesen L, Pan Y (2012) Trinocular disparity processor using a hierarchic classification structure. In: IEEE\/IFIP 20th international conference on VLSI And system-on-chip (VLSI-SoC), 2012. IEEE, pp 247\u2013250"},{"key":"3932_CR21","unstructured":"Park MG, Yoon KJ (2015) Leveraging stereo matching with learning-based confidence measures. In: CVPR, pp 101\u2013109"},{"key":"3932_CR22","unstructured":"Peris M, Maki A, Martull S, Ohkawa Y, Fukui K (2012) Towards a simulation driven stereo vision system. In: ICPR. IEEE, pp 1038\u20131042"},{"issue":"1-3","key":"3932_CR23","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1023\/A:1014573219977","volume":"47","author":"D Scharstein","year":"2002","unstructured":"Scharstein D, Szeliski R (2002) A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. IJCV 47(1-3):7\u201342","journal-title":"IJCV"},{"key":"3932_CR24","doi-asserted-by":"crossref","unstructured":"Spangenberg R, Langner T, Rojas R (2013) Weighted semi-global matching and center-symmetric census transform for robust driver assistance. In: Computer analysis of images and patterns. Springer, pp 34\u201341","DOI":"10.1007\/978-3-642-40246-3_5"},{"key":"3932_CR25","doi-asserted-by":"crossref","unstructured":"Spyropoulos A, Komodakis N, Mordohai P (2014) Learning to detect ground control points for improving the accuracy of stereo matching. In: CVPR. IEEE, pp 1621\u20131628","DOI":"10.1109\/CVPR.2014.210"},{"issue":"7","key":"3932_CR26","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1109\/TPAMI.2003.1206509","volume":"25","author":"J Sun","year":"2003","unstructured":"Sun J, Zheng NN, Shum HY (2003) Stereo matching using belief propagation. TPAMI 25(7):787\u2013 800","journal-title":"TPAMI"},{"key":"3932_CR27","doi-asserted-by":"crossref","unstructured":"Vedula S, Baker S, Rander P, Collins R, Kanade T (1999) Three-dimensional scene flow. In: The proceedings of the seventh IEEE international conference on computer vision, 1999, vol 2. IEEE, pp 722\u2013729","DOI":"10.1109\/ICCV.1999.790293"},{"key":"3932_CR28","doi-asserted-by":"crossref","unstructured":"Yamaguchi K, McAllester D, Urtasun R (2013) Robust monocular epipolar flow estimation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1862\u20131869","DOI":"10.1109\/CVPR.2013.243"},{"key":"3932_CR29","doi-asserted-by":"crossref","unstructured":"Yamaguchi K, McAllester D, Urtasun R (2014) Efficient joint segmentation, occlusion labeling, stereo and flow estimation. In: European conference on computer vision. Springer, pp 756\u2013771","DOI":"10.1007\/978-3-319-10602-1_49"},{"key":"3932_CR30","doi-asserted-by":"crossref","unstructured":"Zagoruyko S, Komodakis N (2015) Learning to compare image patches via convolutional neural networks. CVPR","DOI":"10.1109\/CVPR.2015.7299064"},{"key":"3932_CR31","doi-asserted-by":"crossref","unstructured":"\u017ebontar J, LeCun Y (2015) Computing the stereo matching cost with a convolutional neural network. CVPR","DOI":"10.1109\/CVPR.2015.7298767"},{"key":"3932_CR32","first-page":"1","volume":"17","author":"J Zbontar","year":"2016","unstructured":"Zbontar J, LeCun Y (2016) Stereo matching by training a convolutional neural network to compare image patches. J Mach Learn Res 17:1\u201332","journal-title":"J Mach Learn Res"},{"key":"3932_CR33","doi-asserted-by":"crossref","unstructured":"Zheng L, Wang S, Tian L, He F, Liu Z, Tian Q (2015) Query-adaptive late fusion for image search and person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1741\u20131750","DOI":"10.1109\/CVPR.2015.7298783"},{"key":"3932_CR34","unstructured":"Zheng L, Zhang H, Sun S et al (2016) Person re-identification in the wild. arXiv: 1604.02531"},{"key":"3932_CR35","unstructured":"Zhong Z, Lei M, Li S, Fan J (2016) Re-ranking object proposals for object detection in automatic driving. arXiv: 1605.05904"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-016-3932-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-016-3932-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-016-3932-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T17:39:02Z","timestamp":1568396342000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-016-3932-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,9,22]]},"references-count":35,"journal-issue":{"issue":"18","published-print":{"date-parts":[[2017,9]]}},"alternative-id":["3932"],"URL":"https:\/\/doi.org\/10.1007\/s11042-016-3932-y","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2016,9,22]]}}}