{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T03:53:44Z","timestamp":1777694024738,"version":"3.51.4"},"reference-count":32,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ICA"],"published-print":{"date-parts":[[2019,4,28]]},"DOI":"10.3233\/ica-180597","type":"journal-article","created":{"date-parts":[[2019,3,26]],"date-time":"2019-03-26T16:39:39Z","timestamp":1553618379000},"page":"257-271","source":"Crossref","is-referenced-by-count":1,"title":["Cell-based shape reconstruction from incomplete silhouettes"],"prefix":"10.1177","volume":"26","author":[{"given":"Maarten","family":"Slembrouck","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Veelaert","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dimitri","family":"Van Cauwelaert","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Van Hamme","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wilfried","family":"Philips","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/ICA-180597_ref1","unstructured":"Slembrouck M, Van Cauwelaert D, Van Hamme D, Van Haerenborgh D, Van Hese P, Veelaert P, et al. Self-learning voxel-based multi-camera occlusion maps for 3D reconstruction. In: International Conference on Computer Vision Theory and Applications, Proceedings. SCITEPRESS, 2014, p. 8."},{"key":"10.3233\/ICA-180597_ref2","doi-asserted-by":"crossref","unstructured":"Slembrouck M, Van Cauwelaert D, Veelaert P, Philips W. Shape-from-silhouettes algorithm with built-in occlusion detection and removal. In: International Conference on Computer Vision Theory and Applications, Proceedings. SCITEPRESS, 2015.","DOI":"10.5220\/0005355506350642"},{"key":"10.3233\/ICA-180597_ref3","doi-asserted-by":"crossref","unstructured":"Slembrouck M, Veelaert P, Van Hamme D, Van Cauwelaert D, Philips W. Cell-based approach for 3D reconstruction from incomplete silhouettes. In: P. and Veelaert. Springer. 2017, p. 12.","DOI":"10.1007\/978-3-319-70353-4_45"},{"key":"10.3233\/ICA-180597_ref4","unstructured":"Kang SB, Szeliski R, Chai J. Handling occlusions in dense multi-view stereo. In: Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on. vol. 1. IEEE, 2001. pp. 1-103."},{"key":"10.3233\/ICA-180597_ref5","doi-asserted-by":"crossref","unstructured":"Wegner K, Stankiewicz O, Doma\u0144ski M. Occlusion handling in depth estimation from multiview video. In: Signals and Electronic Systems (ICSES), 2014 International Conference on. IEEE, 2014, pp. 1-4.","DOI":"10.1109\/ICSES.2014.6948712"},{"issue":"7","key":"10.3233\/ICA-180597_ref6","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1109\/34.865184","article-title":"A cooperative algorithm for stereo matching and occlusion detection","volume":"22","author":"Zitnick","year":"2000","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence."},{"key":"10.3233\/ICA-180597_ref7","unstructured":"Sun J, Li Y, Kang SB, Shum HY. Symmetric stereo matching for occlusion handling. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR\u201905). vol. 2. IEEE, 2005. pp. 399-406."},{"key":"10.3233\/ICA-180597_ref8","unstructured":"Ding P, Song Y. Robust object tracking using color and depth images with a depth based occlusion handling and recovery. In: Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on. IEEE, 2015. pp. 930-935."},{"key":"10.3233\/ICA-180597_ref9","first-page":"1","article-title":"Geometry based three-dimensional image processing method for electronic cluster eye","author":"Wu","year":"2018","journal-title":"Integrated Computer-Aided Engineering."},{"key":"10.3233\/ICA-180597_ref10","doi-asserted-by":"crossref","unstructured":"Favaro P, Duci A, Ma Y, Soatto S. On exploiting occlusions in multiple-view geometry. In: Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on. IEEE, 2003. pp. 479-486.","DOI":"10.1109\/ICCV.2003.1238386"},{"key":"10.3233\/ICA-180597_ref11","doi-asserted-by":"crossref","unstructured":"Xiang Y, Savarese S. Object Detection by 3D Aspectlets and Occlusion Reasoning. In: 2013 IEEE International Conference on Computer Vision Workshops, 2013. pp. 530-537.","DOI":"10.1109\/ICCVW.2013.75"},{"key":"10.3233\/ICA-180597_ref12","doi-asserted-by":"crossref","unstructured":"Girshick RB, Felzenszwalb PF, Mcallester DA. Object detection with grammar models. In: Advances in Neural Information Processing Systems, 2011, pp. 442-450.","DOI":"10.1109\/CVPR.2010.5539906"},{"key":"10.3233\/ICA-180597_ref13","doi-asserted-by":"crossref","unstructured":"Mathias M, Benenson R, Timofte R, Van Gool L. Handling occlusions with franken-classifiers. In: Proceedings of the IEEE International Conference on Computer Vision, 2013, pp. 1505-1512.","DOI":"10.1109\/ICCV.2013.190"},{"key":"10.3233\/ICA-180597_ref14","doi-asserted-by":"crossref","unstructured":"Duan G, Ai H, Lao S. A structural filter approach to human detection. In: European Conference on Computer Vision. Springer, 2010, pp. 238-251.","DOI":"10.1007\/978-3-642-15567-3_18"},{"key":"10.3233\/ICA-180597_ref15","unstructured":"Ouyang W, Wang X. A discriminative deep model for pedestrian detection with occlusion handling. In: Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. IEEE, 2012, pp. 3258-3265."},{"key":"10.3233\/ICA-180597_ref16","unstructured":"Ouyang W, Zeng X, Wang X. Partial occlusion handling in pedestrian detection with a deep model, 2015."},{"key":"10.3233\/ICA-180597_ref17","doi-asserted-by":"crossref","unstructured":"Possegger H, Mauthner T, Roth PM, Bischof H. Occlusion Geodesics for Online Multi-Object Tracking. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.","DOI":"10.1109\/CVPR.2014.170"},{"key":"10.3233\/ICA-180597_ref18","doi-asserted-by":"crossref","unstructured":"Top\u00e7u O, Alatan AA, Ercan AO. Occlusion-aware 3D multiple object tracker with two cameras for visual surveillance. In: Advanced Video and Signal Based Surveillance (AVSS), 2014 11th IEEE International Conference on, 2014. pp. 56-61.","DOI":"10.1109\/AVSS.2014.6918644"},{"issue":"7","key":"10.3233\/ICA-180597_ref19","doi-asserted-by":"crossref","first-page":"982","DOI":"10.3390\/s16070982","article-title":"Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System","volume":"16","author":"Jung","year":"2016","journal-title":"Sensors."},{"key":"10.3233\/ICA-180597_ref20","unstructured":"Otsuka K, Mukawa N. Multiview occlusion analysis for tracking densely populated objects based on 2-D visual angles. In: Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on. vol. 1, 2004. p. I\u201390-I\u201397."},{"key":"10.3233\/ICA-180597_ref21","unstructured":"Ess A, Schindler K, Leibe B, Van Gool L. Improved multi-person tracking with active occlusion handling. In: ICRA Workshop on People Detection and Tracking. vol. 2 Citesee, 2009."},{"key":"10.3233\/ICA-180597_ref22","doi-asserted-by":"crossref","unstructured":"Toyoura M, Iiyama M, Funatomi T, Kakusho K, Minoh M. 3d shape reconstruction from incomplete silhouettes in multiple frames. In: Pattern Recognition, 2008. ICPR 2008. 19th International Conference on. IEEE, 2008. pp. 1-4.","DOI":"10.1109\/ICPR.2008.4761591"},{"key":"10.3233\/ICA-180597_ref23","doi-asserted-by":"crossref","unstructured":"Guan L, Sinha S, Franco JS, Pollefeys M. Visual hull construction in the presence of partial occlusion. In: 3D Data Processing, Visualization, and Transmission, Third International Symposium on. IEEE, 2006. pp. 413-420.","DOI":"10.1109\/3DPVT.2006.147"},{"issue":"2","key":"10.3233\/ICA-180597_ref24","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.cviu.2008.02.006","article-title":"Shape from inconsistent silhouette","volume":"112","author":"Landabaso","year":"2008","journal-title":"Computer Vision and Image Understanding."},{"issue":"9","key":"10.3233\/ICA-180597_ref25","doi-asserted-by":"crossref","first-page":"1354","DOI":"10.1016\/j.imavis.2010.01.016","article-title":"Shape from incomplete silhouettes based on the reprojection error","volume":"28","author":"Haro","year":"2010","journal-title":"Image and Vision Computing."},{"issue":"9","key":"10.3233\/ICA-180597_ref26","doi-asserted-by":"crossref","first-page":"3245","DOI":"10.1016\/j.patcog.2012.03.012","article-title":"An octree-based method for shape from inconsistent silhouettes","volume":"45","author":"D\u00edaz-M\u00e1s","year":"2012","journal-title":"Pattern Recognition."},{"issue":"6","key":"10.3233\/ICA-180597_ref27","doi-asserted-by":"crossref","first-page":"2119","DOI":"10.1016\/j.patcog.2010.01.001","article-title":"Shape from silhouette using Dempster \u2013 Shafer theory","volume":"43","author":"D\u00edaz-M\u00e1s","year":"2010","journal-title":"Pattern Recognition."},{"key":"10.3233\/ICA-180597_ref28","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.ins.2014.11.026","article-title":"Cluster-Based Population Initialization for differential evolution frameworks","volume":"297","author":"Poikolainen","year":"2015","journal-title":"Information Sciences."},{"issue":"2","key":"10.3233\/ICA-180597_ref29","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1109\/34.273735","article-title":"The visual hull concept for silhouette-based image understanding","volume":"16","author":"Laurentini","year":"1994","journal-title":"Pattern Analysis and Machine Intelligence, IEEE Transactions on."},{"key":"10.3233\/ICA-180597_ref30","unstructured":"Bradski G. The OpenCV Library. Dr Dobb\u2019s Journal of Software Tools, 2000."},{"key":"10.3233\/ICA-180597_ref31","unstructured":"Rusu RB, Cousins S. 3D is here: Point Cloud Library (PCL). In: IEEE International Conference on Robotics and Automation (ICRA). Shanghai, China, 2011."},{"issue":"3","key":"10.3233\/ICA-180597_ref32","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/MCG.2007.68","article-title":"Surface capture for performance-based animation","volume":"27","author":"Starck","year":"2007","journal-title":"Computer Graphics and Applications, IEEE."}],"container-title":["Integrated Computer-Aided Engineering"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/ICA-180597","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:14:16Z","timestamp":1777454056000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/ICA-180597"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,28]]},"references-count":32,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/ica-180597","relation":{},"ISSN":["1069-2509","1875-8835"],"issn-type":[{"value":"1069-2509","type":"print"},{"value":"1875-8835","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,28]]}}}