Abstract
The motion field from image sequences of a dynamic 3D scene is in general piecewise continuous. Since two neighbouring regions may have completely different motions, motion estimation at the discontinuities is problematic. In particular spatial averaging of motion vectors is inappropriate at such positions. We avoid this problem by channel encoding brightness change constraint equations (BCCE) for each spatial position into a channel matrix. By spatial averaging of this channel representation and subsequently decoding we are able to estimate all significantly different motions occurring at the discontinuity, as well as their covariances. This paper extends and improves this multiple motion estimation scheme by locally selecting the appropriate scale for the spatial averaging.
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References
Jepson, A., Black, M.: Mixture models for optical flow. Technical Report RBCV-TR-93-44, Res. in Biol. and Comp. Vision, Dept. of Comp. Sci., Univ. of Toronto (1993)
Granlund, G.H., Knutsson, H.: Signal Processing for Computer Vision. Kluwer Academic Publishers, Dordrecht (1995)
Ayer, S., Sawhney, H.S.: Layered representation of motion video using robust maximum-likelihood estimation of mixture models and MDL encoding. In: Proceedings of the fifth International Conference on Computer Vision (1995)
Spies, H., Forssén, P.E.: Two-dimensional channel representation for multiple velocities. In: Bigun, J., Gustavsson, T. (eds.) SCIA 2003. LNCS, vol. 2749, pp. 356–362. Springer, Heidelberg (2003)
Shizawa, M., Mase, K.: Simultaneous multiple optical flow estimation. In: ICPR, Atlantic City, NJ, USA, pp. 274–278 (1990)
Nestares, O., Navarro, R.: Probabilistic estimation of optical flow in multiple band-pass directional channels. Image and Vision Comp. 19, 339–351 (2001)
Mota, C., Stuke, I., Barth, E.: Analytic solutions for multiple motions. In: ICIP, vol. 2, pp. 917–920. Thessaloniki, Greece (2001)
Andersson, K., Knutsson, H.: Multiple hierarchical motion estimation. In: SPPRA, Crete, Greece, pp. 80–85 (2002)
Beauchemin, S.S., Barron, J.L.: On the fourier properties of discontinuous motion. Journal of Mathematical Imaging and Vision 13, 155–172 (2000)
Forssén, P.E.: Low and Medium Level Vision using Channel Representations. PhD thesis, Linköping University, Sweden, SE-581 83 Linköping, Sweden, Dissertation No. 858 (2004)
Granlund, G.H.: An associative perception-action structure using a localized space variant information representation. In: Proceedings of Algebraic Frames for the Perception-Action Cycle (AFPAC), Kiel, Germany (2000)
Nordberg, K., Granlund, G., Knutsson, H.: Representation and Learning of Invariance (also as Technical Report LiTH-ISY-R-1552). In: Proceedings of IEEE International Conference on Image Processing, Austin, Texas. IEEE Press, Los Alamitos (1994)
Weiss, Y., Fleet, D.: Velocity likelihoods in biological and machine vision. In: Rao, R.P.N., Olshausen, B.A., Lewicki, M.S (eds.) Probabilistic Models of the Brain: Perception and Neural Function, pp. 81–100. MIT Press, Cambridge (2001)
Lucas, B., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: DARPA Image Understanding Workshop, pp. 121–130 (1981)
Weickert, J., Scharr, H.: A scheme for coherence-enhancing diffusion filtering with optimized rotation invariance. J. Visual Communication and Image Representation 13, 103–118 (2002)
Felsberg, M.: Optical flow estimation from monogenic phase. In: IWCM04, Reisensburg, Germany (2004)
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Forssén, PE., Spies, H. (2007). Multiple Motion Estimation Using Channel Matrices. In: Jähne, B., Mester, R., Barth, E., Scharr, H. (eds) Complex Motion. IWCM 2004. Lecture Notes in Computer Science, vol 3417. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69866-1_5
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DOI: https://doi.org/10.1007/978-3-540-69866-1_5
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