The Structure of Multiplicative Motions in Natural Imagery
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[1] David J. Fleet,et al. Performance of optical flow techniques , 1994, International Journal of Computer Vision.
[2] A. Mackay. "Textures" , 1987 .
[3] Keith Langley,et al. Computational analysis of non-Fourier motion , 1994, Vision Research.
[4] Weichuan Yu,et al. Detection and characterization of multiple motion points , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).
[5] M. Shizawa,et al. Principle of superposition: a common computational framework for analysis of multiple motion , 1991, Proceedings of the IEEE Workshop on Visual Motion.
[6] Edward H. Adelson,et al. Ordinal characteristics of transparency. , 1990 .
[7] Shmuel Peleg,et al. A Three-Frame Algorithm for Estimating Two-Component Image Motion , 1992, IEEE Trans. Pattern Anal. Mach. Intell..
[8] Richard Szeliski,et al. Layer extraction from multiple images containing reflections and transparency , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[9] Eero P. Simoncelli,et al. Natural image statistics and neural representation. , 2001, Annual review of neuroscience.
[10] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[11] Ivar Austvoll,et al. A Study of the Yosemite Sequence Used as a Test Sequence for Estimation of Optical Flow , 2005, SCIA.
[12] Weichuan Yu,et al. Multiple motion analysis: in spatial or in spectral domain? , 2003, Comput. Vis. Image Underst..
[13] Richard P. Wildes,et al. Detecting Spatiotemporal Structure Boundaries: Beyond Motion Discontinuities , 2009, ACCV.
[14] A J Ahumada,et al. Model of human visual-motion sensing. , 1985, Journal of the Optical Society of America. A, Optics and image science.
[15] Azriel Rosenfeld,et al. Robust regression methods for computer vision: A review , 1991, International Journal of Computer Vision.
[16] Michael J. Black,et al. Mixture models for optical flow computation , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.
[17] D J Heeger,et al. Model for the extraction of image flow. , 1987, Journal of the Optical Society of America. A, Optics and image science.
[18] E H Adelson,et al. Spatiotemporal energy models for the perception of motion. , 1985, Journal of the Optical Society of America. A, Optics and image science.
[19] Steven S. Beauchemin,et al. The Frequency Structure of One-Dimensional Occluding Image Signals , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[20] Berthold K. P. Horn,et al. Determining Optical Flow , 1981, Other Conferences.
[21] David J. Fleet,et al. Computation of component image velocity from local phase information , 1990, International Journal of Computer Vision.
[22] Weichuan Yu,et al. Çöööòøøø Ëøöù Blockinøùöö Óó Øøø Ç Blockin , 2007 .
[23] David J. Fleet. Measurement of image velocity , 1992 .
[24] Keith Langley,et al. PII: S0042-6989(98)00093-5 , 1998 .
[25] R. Wildes,et al. Early spatiotemporal grouping with a distributed oriented energy representation , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[26] T. Poggio,et al. Visual hyperacuity: spatiotemporal interpolation in human vision , 1981, Proceedings of the Royal Society of London. Series B. Biological Sciences.
[27] Suzanne Beauchemin,et al. The Frequency Structure of 1D Occluding Image Signals , 2000 .
[28] Edward H. Adelson,et al. Human-assisted motion annotation , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[29] Ronald N. Bracewell,et al. The Fourier Transform and Its Applications , 1966 .
[30] Y. J. Tejwani,et al. Robot vision , 1989, IEEE International Symposium on Circuits and Systems,.
[31] F. Harris. On the use of windows for harmonic analysis with the discrete Fourier transform , 1978, Proceedings of the IEEE.
[32] D. Kersten. Transparency and the cooperative computation of scene attributes , 1991 .
[33] Richard Szeliski,et al. A Database and Evaluation Methodology for Optical Flow , 2007, 2007 IEEE 11th International Conference on Computer Vision.