{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T17:10:16Z","timestamp":1770743416476,"version":"3.49.0"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319105895","type":"print"},{"value":"9783319105901","type":"electronic"}],"license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"DOI":"10.1007\/978-3-319-10590-1_28","type":"book-chapter","created":{"date-parts":[[2014,8,13]],"date-time":"2014-08-13T21:50:08Z","timestamp":1407966608000},"page":"423-438","source":"Crossref","is-referenced-by-count":18,"title":["Optical Flow Estimation with Channel Constancy"],"prefix":"10.1007","author":[{"given":"Laura","family":"Sevilla-Lara","sequence":"first","affiliation":[]},{"given":"Deqing","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Erik G.","family":"Learned-Miller","sequence":"additional","affiliation":[]},{"given":"Michael J.","family":"Black","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"28_CR1","doi-asserted-by":"crossref","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) (March 2011), http:\/\/dx.doi.org\/10.1007\/s11263-010-0390-2","DOI":"10.1007\/s11263-010-0390-2"},{"key":"28_CR2","doi-asserted-by":"crossref","unstructured":"Berg, A.C., Malik, J.: Geometric blur for template matching. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol.\u00a01. IEEE, pp. I\u2013607 (2001)","DOI":"10.1109\/CVPR.2001.990529"},{"issue":"1","key":"28_CR3","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1006\/cviu.1996.0006","volume":"63","author":"M.J. Black","year":"1996","unstructured":"Black, M.J., Anandan, P.: The robust estimation of multiple motions: Parametric and piecewise-smooth flow fields. Computer Vision and Image Understanding\u00a063(1), 75\u2013104 (1996)","journal-title":"Computer Vision and Image Understanding"},{"key":"28_CR4","doi-asserted-by":"crossref","unstructured":"Brox, T., Malik, J.: Large displacement optical flow: Descriptor matching in variational motion estimation. PAMI\u00a033(3) (2011), http:\/\/lmb.informatik.uni-freiburg.de\/\/Publications\/2011\/Bro11a","DOI":"10.1109\/TPAMI.2010.143"},{"issue":"3","key":"28_CR5","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1023\/B:VISI.0000045324.43199.43","volume":"61","author":"A. Bruhn","year":"2005","unstructured":"Bruhn, A., Weickert, J., Schn\u00f6rr, C.: Lucas\/Kanade meets Horn\/Schunck: Combining local and global optic flow methods. IJCV\u00a061(3), 211\u2013231 (2005)","journal-title":"IJCV"},{"issue":"4","key":"28_CR6","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1109\/TCOM.1983.1095851","volume":"31","author":"P.J. Burt","year":"1983","unstructured":"Burt, P.J., Adelson, E.H.: The Laplacian pyramid as a compact image code. IEEE Transactions on Communications\u00a031(4), 532\u2013540 (1983)","journal-title":"IEEE Transactions on Communications"},{"key":"28_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/978-3-642-33783-3_44","volume-title":"Computer Vision \u2013 ECCV 2012","author":"D.J. Butler","year":"2012","unstructured":"Butler, D.J., Wulff, J., Stanley, G.B., Black, M.J.: A naturalistic open source movie for optical flow evaluation. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part VI. LNCS, vol.\u00a07577, pp. 611\u2013625. Springer, Heidelberg (2012)"},{"key":"28_CR8","doi-asserted-by":"crossref","unstructured":"Charbonnier, P., Blanc-Feraud, L., Aubert, G., Barlaud, M.: Two deterministic half-quadratic regularization algorithms for computed imaging. In: IEEE Int. Conf. Image Proc. (ICIP), vol.\u00a02, pp. 168\u2013172 (1994)","DOI":"10.1109\/ICIP.1994.413553"},{"key":"28_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"808","DOI":"10.1007\/978-3-642-02256-2_67","volume-title":"Scale Space and Variational Methods in Computer Vision","author":"M. Felsberg","year":"2009","unstructured":"Felsberg, M.: Spatio-featural scale-space. In: Tai, X.-C., M\u00f8rken, K., Lysaker, M., Lie, K.-A. (eds.) SSVM 2009. LNCS, vol.\u00a05567, pp. 808\u2013819. Springer, Heidelberg (2009)"},{"key":"28_CR10","doi-asserted-by":"crossref","unstructured":"Felsberg, M.: Adaptive filtering using channel representations. In: Mathematical Methods for Signal and Image Analysis and Representation, pp. 31\u201348. Springer (2012)","DOI":"10.1007\/978-1-4471-2353-8_2"},{"issue":"2","key":"28_CR11","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/TPAMI.2006.29","volume":"28","author":"M. Felsberg","year":"2006","unstructured":"Felsberg, M., Forss\u00e9n, P.E., Scharr, H.: Channel smoothing: Efficient robust smoothing of low-level signal features. PAMI\u00a028(2), 209\u2013222 (2006)","journal-title":"PAMI"},{"key":"28_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1007\/10722492_3","volume-title":"Algebraic Frames for the Perception-Action Cycle","author":"G.H. Granlund","year":"2000","unstructured":"Granlund, G.H.: An associative perception-action structure using a localized space variant information representation. In: Sommer, G., Zeevi, Y.Y. (eds.) AFPAC 2000. LNCS, vol.\u00a01888, pp. 48\u201368. Springer, Heidelberg (2000)"},{"issue":"6","key":"28_CR13","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1109\/34.927465","volume":"23","author":"H.W. Haussecker","year":"2001","unstructured":"Haussecker, H.W., Fleet, D.J.: Computing optical flow with physical models of brightness variation. IEEE Trans. Pattern Anal. Mach. Intell.\u00a023(6), 661\u2013673 (2001), http:\/\/dx.doi.org\/10.1109\/34.927465","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"28_CR14","unstructured":"Horn, B.K., Schunck, B.G.: Determining optical flow. Tech. rep., Massachusetts Institute of Technology, Cambridge, MA, USA (1980)"},{"key":"28_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-540-73040-8_1","volume-title":"Image Analysis","author":"E. Jonsson","year":"2007","unstructured":"Jonsson, E., Felsberg, M.: Accurate interpolation in appearance-based pose estimation. In: Ersb\u00f8ll, B.K., Pedersen, K.S. (eds.) SCIA 2007. LNCS, vol.\u00a04522, pp. 1\u201310. Springer, Heidelberg (2007), http:\/\/dx.doi.org\/10.1007\/978-3-540-73040-8_1"},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Jonsson, E., Felsberg, M.: Efficient computation of channel-coded feature maps through piecewise polynomials. Image and Vision Computing\u00a027(11) (2009)","DOI":"10.1016\/j.imavis.2008.11.002"},{"issue":"2-3","key":"28_CR17","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1023\/A:1008065931878","volume":"31","author":"J.J. Koenderink","year":"1999","unstructured":"Koenderink, J.J., Van Doorn, A.J.: The structure of locally orderless images. International Journal of Computer Vision\u00a031(2-3), 159\u2013168 (1999)","journal-title":"International Journal of Computer Vision"},{"key":"28_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1007\/978-3-540-88690-7_3","volume-title":"Computer Vision \u2013 ECCV 2008","author":"C. Liu","year":"2008","unstructured":"Liu, C., Yuen, J., Torralba, A., Sivic, J., Freeman, W.T.: SIFT flow: Dense correspondence across different scenes. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol.\u00a05304, pp. 28\u201342. Springer, Heidelberg (2008), http:\/\/dx.doi.org\/10.1007\/978-3-540-88690-7_3"},{"key":"28_CR19","doi-asserted-by":"crossref","unstructured":"Mears, B., Sevilla-Lara, L., Learned-Miller, E.: Distribution fields with adaptive kernels for large displacement image alignment. In: BMVC. IEEE (2013)","DOI":"10.5244\/C.27.17"},{"key":"28_CR20","unstructured":"Nordberg, K., Granlund, G., Knutsson, H.: Representation and Learning of Invariance. Report LiTH-ISY-I-1552, Computer Vision Laboratory, SE-581 83 Link\u00f6ping, Sweden (1994)"},{"key":"28_CR21","doi-asserted-by":"crossref","unstructured":"Oron, S., Bar-Hillel, A., Levi, D., Avidan, S.: Locally orderless tracking. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1940\u20131947. IEEE (2012)","DOI":"10.1109\/CVPR.2012.6247895"},{"key":"28_CR22","unstructured":"Sevilla-Lara, L., Learned-Miller, E.: Distribution fields. Tech. rep., UMass Amherst (2011)"},{"key":"28_CR23","doi-asserted-by":"crossref","unstructured":"Sevilla-Lara, L., Learned-Miller, E.: Distribution fields for tracking. In: CVPR (2012)","DOI":"10.1109\/CVPR.2012.6247891"},{"issue":"6","key":"28_CR24","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1007\/BF00204120","volume":"66","author":"H.P. Snippe","year":"1992","unstructured":"Snippe, H.P., Koenderink, J.J.: Discrimination thresholds for channel-coded systems. Biological Cybernetics\u00a066(6), 543\u2013551 (1992)","journal-title":"Biological Cybernetics"},{"key":"28_CR25","doi-asserted-by":"crossref","unstructured":"Steinbrucker, F., Pock, T., Cremers, D.: Large displacement optical flow computation without warping. In: ICCV (2009)","DOI":"10.1109\/ICCV.2009.5459364"},{"key":"28_CR26","unstructured":"Steinbruecker, F., Pock, T., Cremers, D.: Advanced data terms for variational optic flow estimation. In: Proceedings Vision, Modeling and Visualization (2009)"},{"issue":"2","key":"28_CR27","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/s11263-013-0644-x","volume":"106","author":"D. Sun","year":"2014","unstructured":"Sun, D., Roth, S., Black, M.J.: A quantitative analysis of current practices in optical flow estimation and the principles behind them. International Journal of Computer Vision (IJCV)\u00a0106(2), 115\u2013137 (2014)","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"28_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1007\/978-3-540-88690-7_7","volume-title":"Computer Vision \u2013 ECCV 2008","author":"D. Sun","year":"2008","unstructured":"Sun, D., Roth, S., Lewis, J.P., Black, M.J.: Learning optical flow. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol.\u00a05304, pp. 83\u201397. Springer, Heidelberg (2008)"},{"key":"28_CR29","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1007\/3-540-48236-9_2","volume-title":"Scale-Space Theories in Computer Vision","author":"B. Ginneken van","year":"1999","unstructured":"van Ginneken, B., ter Haar Romeny, B.M.: Applications of locally orderless images. In: Nielsen, M., Johansen, P., Fogh Olsen, O., Weickert, J. (eds.) Scale-Space 1999. LNCS, vol.\u00a01682, pp. 10\u201321. Springer, Heidelberg (1999)"},{"key":"28_CR30","doi-asserted-by":"crossref","unstructured":"Weber, J., Malik, J., Devadas, S., Michel, P.: Robust computation of optical flow in a multi-scale differential framework. IJCV\u00a014 (1994)","DOI":"10.1007\/BF01421489"},{"key":"28_CR31","doi-asserted-by":"crossref","unstructured":"Weinzaepfel, P., Revaud, J., Harchaoui, Z., Schmid, C.: Deepflow: Large displacement optical flow with deep matching. In: ICCV, pp. 1385\u20131392 (2013)","DOI":"10.1109\/ICCV.2013.175"},{"key":"28_CR32","unstructured":"Werlberger, M.: Convex Approaches for High Performance Video Processing. Ph.D. thesis, Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria (June 2012), http:\/\/gpu4vision.icg.tugraz.at\/papers\/2012\/werlberger_phd.pdf"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2014"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-10590-1_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T05:26:43Z","timestamp":1746336403000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-10590-1_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"ISBN":["9783319105895","9783319105901"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-10590-1_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014]]}}}