P. J. Burt, C. Yen, and X. Xu, "Multiresolution Flow-Through Motion Analysis". In Proceedings of the 1983 IEEE Conference on Computer Vision and Pattern Recognition.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....then after compensating for the translation the full 66 a#ne motion estimation is performed. Since the motion compensation is applied at the tile level, rather than at the pixel level, it is at the same time making use of knowledge regarding the success of pyramidal coarse fine alignment schemes [7]. Usually a gaussian pyramid scheme is applied in order to increase the range of the motion estimation process; however, a simpler yet e#ective scheme is carried out by making simultaneous use of tile motion estimates and pixel statistics. For each pair of reference and target locales, the ....

P.J. Burt, C. Yen, and X.Xu. Multi-resolution flow through motion analysis. In Proc. IEEE Conf. On Computer Vision and Pattern Recognition, pages 246--252, 1983.

....is based on the assumption that phase is preserved [16] In this case the phase response for spatiotemporal frequencies is computed using energy filters and then the spatial and temporal derivatives of the phase are estimated to obtain one dimensional motion components. Correlation techniques [6, 8, 33, 56] have mostly been used in the processing of stereo images where one component of the displacement is defined by the epipolar constraint, and to establish sparse feature correspondence when far apart views obtained by a moving camera are considered (discrete motion) They have also been used to ....

P. J. Burt, C. Yen, and X. Xu. Multi-resolution flow through motion analysis. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, pages 246--252, 1983.

....system has to be translated into 3 D scene motion. Our approach is to initially compute local optic flow fields that measure image velocity at each pixel in the image. A variety of techniques for computing optic flow fields have been used with varying results including matching based techniques [5, 11, 40], gradient based techniques [23, 33, 12] and spatio temporal energy methods [21, 2] Optic flow was chosen as the primitive upon which to base the tracking algorithm for the following reasons: ffl The ability to track an object in three dimensions implies that there will be motion across the ....

P. J. Burt, C. Yen, and X. Xu. Multi-resolution flow-through motion analysis. In Proceedings of the IEEE CVPR Conference, pages 246--252, 1983.

....a small window in the first image is searched for a corresponding window in the next image, where the search criterion is maximal cross correlation. The cross correlation, which is a measure of similarity, is usually applied to low pass filtered [Wong and Hall, 1978] or band pass filtered images [Burt et al. 1983; Anandan, 1989; Anandan and Weiss, 1985] A third group of local image motion estimation techniques computes velocity in spatio temporal frequency space [Watson and Ahumada, 1985; Adelson and Bergen, 1985; Fleet and Jepson, 1990; Heeger, 1988] Similar to the optical flow constraint equation, in ....

P.J. Burt, C. Yen, and X. Xu. Multi-resolution flow through motion analysis. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, pages 246--252, 1983.

....Matching Accurate numerical differentiation may be impractical because of noise, because a small number of frames exist or because of aliasing in the image acquisition process. In these cases differential approaches may be inappropriate and it is natural to turn to region based matching [25, 6, 14, 38, 39]. Such approaches define velocity v as the shift d = d x ; d y ) that yields the best fit between image regions at different times. Finding the best match amounts to maximizing a similarity measure (over d) such as the normalized crosscorrelation or minimizing a distance measure, such as the ....

Burt P.J., Yen C. and Xu X. (1983) Multiresolution flow-through motion analysis. Proc. IEEE CVPR, Washington, pp. 246-252

....was then followed by a great number of contributions that proposed alternative methods. To mention a few, we can cite the spatiotemporal filtering methods, initiated by Adelson and Bergen [1] that split in energy based methods [15] and phase based methods [13] and region matching methods [8] [9] [3] See Barron, Fleet and Beauchemin [4] for an extensive review of these methods [4] Many authors noticed that a good way to enhance the reliability of optic flow estimation was to perform a multi scale computation. The multi scale approach proved to be very powerful. In matching methods, it ....

....a unique minimum. As such however, this method cannot be used to estimate wide ranges of displacements. Methods based on spatiotemporal filtering or velocity tuned filters [7] 10] 13] 14] 15] also assume that the flow is constant over the support of their filters. Block matching methods [3] [9] rely on the assumption that the motion is constant over small windows of the picture. We make no exception to this rule and have to do a similar assumption to extract the optic flow. In this paper, our way around aperture is the following: we define some measure functions ( n ) n=1: N of L 2 ....

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P.J. Burt, C. Yen, and X. Xu. Multiresolution flow--through motion analysis. In Proc. Conference Computer Vision and Pattern Recognition, pages 246--252, Washington, 1983.

....system has to be translated into 3 D scene motion. Our approach is to initially compute local optic flow fields that measure image velocity at each pixel in the image. A variety of techniques for computing optic flow fields have been used with varying results including matching based techniques [3, 10, 31], gradient based techniques [11, 18, 27] and spatio temporal energy methods [1, 16] Optic flow was chosen as the primitive upon which to base the tracking algorithm for the following reasons: # The ability to track an object in three dimensions implies that there will be motion across the ....

Burt, P. J., C. Yen, and X. Xu, "Multiresolution flow-through motion analysis," Proceedings of the IEEE CVPR Conference, pp. 246-252, 1983.

....pyramid of image resolutions. Such hierarchical processing may also allow handling rapid motion since reducing high frequency image content allows to perform matching at larger displacements [29] The hierarchical extension Various multiresolution methods have been proposed for motion estimation [5][13] 29] One class of such methods is based on a non recursive multigrid (coarseto fine resolution) approach [29] It consists of generating a pyramid of varying image resolutions from the lowest resolution at the top level (k = L) to the full resolution at the bottom level (k = 0) of the ....

P. J. Burt and et al., "Multi-Resolution Flow-Through Motion Analysis," Proc. Conf. Computer Vision and Pattern Recognition, pp. 246--252, June 1983.

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P. J. Burt, C. Yen, and X. Xu, "Multiresolution Flow-Through Motion Analysis". In Proceedings of the 1983 IEEE Conference on Computer Vision and Pattern Recognition.

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P.J. Burt, C. Yen, and X.Xu, "Multi-resolution flow through motion analysis," CVPR83, pp. 246-252, 1983.

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P. J. Burt, C. Yen, and X. Xu, "Multi-resolution flow-through motion analysis," in Proc. IEEE CVPR Conf., pp. 246--252, 1983.

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P. J. Burt, C. Yen and X. Xu, "Multi-resolution flow-through motion analysis", IEEE Conference on Computer Vision and Pattern Recognition, pp. 246-252., June 1983.

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