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Unlike previous work that addressed this problem, we do not rely on locally convergent optimization but present a system that can handle fast motion, temporally disrupted input, and can correctly match objects that disappear for extended time periods in acquisition holes due to occlusion. Our approach is motivated by cartography: We first estimate a few landmark correspondences, which are extended to a dense matching and then used to reconstruct geometry and motion. We propose a number of algorithmic building blocks: a scheme for tracking landmarks in temporally coherent and incoherent data, an algorithm for robust estimation of dense correspondences under topological noise, and the integration of local matching techniques to refine the result. We describe and evaluate the individual components and propose a complete animation reconstruction pipeline based on these ideas. We evaluate our method on a number of standard benchmark datasets and show that we can obtain correct reconstructions in situations where other techniques fail completely or require additional user guidance such as a template model.<\/jats:p>","DOI":"10.1145\/2159516.2159517","type":"journal-article","created":{"date-parts":[[2012,5,1]],"date-time":"2012-05-01T13:43:38Z","timestamp":1335879818000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":66,"title":["Animation cartography\u2014intrinsic reconstruction of shape and motion"],"prefix":"10.1145","volume":"31","author":[{"given":"Art","family":"Tevs","sequence":"first","affiliation":[{"name":"Max-Planck Institut Informatik, and Saarland University, Germany"}]},{"given":"Alexander","family":"Berner","sequence":"additional","affiliation":[{"name":"Max-Planck Institut Informatik, and Saarland University, Germany"}]},{"given":"Michael","family":"Wand","sequence":"additional","affiliation":[{"name":"Max-Planck Institut Informatik, and Saarland University, Germany"}]},{"given":"Ivo","family":"Ihrke","sequence":"additional","affiliation":[{"name":"Max-Planck Institut Informatik, and Saarland University, Germany"}]},{"given":"Martin","family":"Bokeloh","sequence":"additional","affiliation":[{"name":"Max-Planck Institut Informatik, and Saarland University, Germany"}]},{"given":"Jens","family":"Kerber","sequence":"additional","affiliation":[{"name":"Max-Planck Institut Informatik, and Saarland University, Germany"}]},{"given":"Hans-Peter","family":"Seidel","sequence":"additional","affiliation":[{"name":"Max-Planck Institut Informatik, and Saarland University, Germany"}]}],"member":"320","published-online":{"date-parts":[[2012,4,30]]},"reference":[{"volume-title":"Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR'08)","author":"Ahmed N.","key":"e_1_2_2_1_1","unstructured":"Ahmed , N. , Theobalt , C. , Rossl , C. , Thrun , S. , and Seidel , H . -P. 2008. Dense correspondence finding for parameterization-free animation reconstruction from video . In Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR'08) . 1--8. Ahmed, N., Theobalt, C., Rossl, C., Thrun, S., and Seidel, H.-P. 2008. Dense correspondence finding for parameterization-free animation reconstruction from video. In Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR'08). 1--8."},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/882262.882311"},{"volume-title":"Proceedings of the Conference on Neural Information Processing Systems (NIPS'04)","author":"Anguelov D.","key":"e_1_2_2_3_1","unstructured":"Anguelov , D. , Srinivasan , P. , Pang , H.-C. , Koller , D. , Thrun , S. , and Davis , J . 2004. The correlated correspondence algorithm for unsupervised registration of nonrigid surfaces . In Proceedings of the Conference on Neural Information Processing Systems (NIPS'04) . 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