{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T11:41:43Z","timestamp":1725795703914},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319079974"},{"type":"electronic","value":"9783319079981"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"DOI":"10.1007\/978-3-319-07998-1_53","type":"book-chapter","created":{"date-parts":[[2014,6,4]],"date-time":"2014-06-04T21:27:22Z","timestamp":1401917242000},"page":"460-467","source":"Crossref","is-referenced-by-count":4,"title":["Sparse Regularization of TV-L1 Optical Flow"],"prefix":"10.1007","author":[{"given":"Joel","family":"Gibson","sequence":"first","affiliation":[]},{"given":"Oge","family":"Marques","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"53_CR1","unstructured":"The Middlebury Computer Vision Pages (2013), http:\/\/vision.middlebury.edu"},{"issue":"1","key":"53_CR2","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/s11263-006-4331-z","volume":"67","author":"J. Aujol","year":"2006","unstructured":"Aujol, J., Gilboa, G., Chan, T., Osher, S.: Structure-texture image decomposition modeling, algorithms, and parameter selection. IJCV\u00a067(1), 111\u2013136 (2006)","journal-title":"IJCV"},{"issue":"3","key":"53_CR3","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1007\/s11263-011-0490-7","volume":"97","author":"A. Ayvaci","year":"2011","unstructured":"Ayvaci, A., Raptis, M., Soatto, S.: Sparse Occlusion Detection with Optical Flow. IJCV\u00a097(3), 322\u2013338 (2011)","journal-title":"IJCV"},{"issue":"1","key":"53_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11263-010-0390-2","volume":"92","author":"S. Baker","year":"2011","unstructured":"Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M.J., Szeliski, R.: A Database and Evaluation Methodology for Optical Flow. IJCV\u00a092(1), 1\u201331 (2011)","journal-title":"IJCV"},{"key":"53_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1137\/090756855","volume":"91125","author":"S. Becker","year":"2011","unstructured":"Becker, S., Bobin, J., Cand\u00e8s, E.: NESTA: A fast and accurate first-order method for sparse recovery. SIAM Journal on Imaging Sciences\u00a091125, 1\u201337 (2011)","journal-title":"SIAM Journal on Imaging Sciences"},{"key":"53_CR6","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1007\/978-3-540-24673-2_3","volume-title":"ECCV 2004","author":"T. Brox","year":"2004","unstructured":"Brox, T., Bruhn, A., Papenberg, N., Weickert, J.: High accuracy optical flow estimation based on a theory for warping. In: Pajdla, T., Matas, J. (eds.) ECCV 2004. LNCS, vol.\u00a03024, pp. 25\u201336. Springer, Heidelberg (2004)"},{"key":"53_CR7","doi-asserted-by":"crossref","unstructured":"Elad, M.: Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, 1st edn. Springer Publishing Company (2010) (incorporated)","DOI":"10.1007\/978-1-4419-7011-4"},{"issue":"12","key":"53_CR8","doi-asserted-by":"publisher","first-page":"3736","DOI":"10.1109\/TIP.2006.881969","volume":"15","author":"M. Elad","year":"2006","unstructured":"Elad, M., Aharon, M.: Image denoising via sparse and redundant representations over learned dictionaries. IEEE Transactions on Image Processing\u00a015(12), 3736\u20133745 (2006)","journal-title":"IEEE Transactions on Image Processing"},{"key":"53_CR9","doi-asserted-by":"crossref","unstructured":"Engan, K., Aase, S.O., Hakon Husoy, J.: Method of optimal directions for frame design. In: Proceedings of the Acoustics, Speech, and Signal Processing, pp. 2443\u20132446 (1999)","DOI":"10.1109\/ICASSP.1999.760624"},{"key":"53_CR10","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/0004-3702(81)90024-2","volume":"17","author":"B. Horn","year":"1981","unstructured":"Horn, B., Schunck, B.: Determining optical flow. Artificial Intelligence\u00a017, 185\u2013203 (1981)","journal-title":"Artificial Intelligence"},{"key":"53_CR11","doi-asserted-by":"crossref","unstructured":"Jia, K., Wang, X., Tang, X.: Optical Flow Estimation Using Learned Sparse Model. In: Proceedings of IEEE International Conference on Computer Vision. No. 60903115 (2011)","DOI":"10.1109\/ICCV.2011.6126522"},{"key":"53_CR12","first-page":"19","volume":"11","author":"J. Mairal","year":"2010","unstructured":"Mairal, J., Bach, F., Ponce, J., Sapiro, G.: Online learning for matrix factorization and sparse coding. The Journal of Machine Learning Research\u00a011, 19\u201360 (2010)","journal-title":"The Journal of Machine Learning Research"},{"issue":"1","key":"53_CR13","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1109\/TIP.2007.911828","volume":"17","author":"J. Mairal","year":"2008","unstructured":"Mairal, J., Elad, M., Sapiro, G.: Sparse representation for color image restoration. IEEE Transactions on Image Processing\u00a017(1), 53\u201369 (2008)","journal-title":"IEEE Transactions on Image Processing"},{"key":"53_CR14","doi-asserted-by":"crossref","unstructured":"Nesterov, Y.: Smooth minimization of non-smooth functions. Mathematical Programming 103, 127\u2013152 (2005)","DOI":"10.1007\/s10107-004-0552-5"},{"key":"53_CR15","doi-asserted-by":"crossref","unstructured":"Shen, X., Wu, Y.: Sparsity model for robust optical flow estimation at motion discontinuities. In: Computer Vision and Pattern Recognition (CVPR), vol.\u00a01, pp. 2456\u20132463. IEEE (2010)","DOI":"10.1109\/CVPR.2010.5539944"},{"key":"53_CR16","doi-asserted-by":"crossref","unstructured":"Sun, D., Roth, S., Black, M.: Secrets of optical flow estimation and their principles. In: Computer Vision and Pattern Recognition (CVPR), pp. 2432\u20132439. IEEE (2010)","DOI":"10.1109\/CVPR.2010.5539939"},{"key":"53_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/978-3-642-03061-1_2","volume-title":"Statistical and Geometrical Approaches to Visual Motion Analysis","author":"A. Wedel","year":"2009","unstructured":"Wedel, A., Pock, T., Zach, C., Bischof, H., Cremers, D.: An Improved Algorithm for TV-L1 Optical Flow. In: Cremers, D., Rosenhahn, B., Yuille, A.L., Schmidt, F.R. (eds.) Statistical and Geometrical Approaches to Visual Motion Analysis. LNCS, vol.\u00a05604, pp. 23\u201345. Springer, Heidelberg (2009)"},{"key":"53_CR18","doi-asserted-by":"crossref","unstructured":"Werlberger, M., Trobin, W., Pock, T., Wedel, A., Cremers, D., Bischof, H.: Anisotropic Huber-L1 optical flow. In: Proceedings of BMVC (2009)","DOI":"10.5244\/C.23.108"}],"container-title":["Lecture Notes in Computer Science","Image and Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-07998-1_53","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,13]],"date-time":"2023-07-13T23:36:24Z","timestamp":1689291384000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-07998-1_53"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"ISBN":["9783319079974","9783319079981"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-07998-1_53","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2014]]}}}