Computation of component image velocity from local phase information

We present a technique for the computation of 2D component velocity from image sequences. Initially, the image sequence is represented by a family of spatiotemporal velocity-tuned linear filters. Component velocity, computed from spatiotemporal responses of identically tuned filters, is expressed in terms of the local first-order behavior of surfaces of constant phase. Justification for this definition is discussed from the perspectives of both 2D image translation and deviations from translation that are typical in perspective projections of 3D scenes. The resulting technique is predominantly linear, efficient, and suitable for parallel processing. Moreover, it is local in space-time, robust with respect to noise, and permits multiple estimates within a single neighborhood. Promising quantiative results are reported from experiments with realistic image sequences, including cases with sizeable perspective deformation.

[1]  Dennis Gabor,et al.  Theory of communication , 1946 .

[2]  L. Rabiner,et al.  A digital signal processing approach to interpolation , 1973 .

[3]  G. Whitham,et al.  Linear and Nonlinear Waves , 1976 .

[4]  Jan J. Koenderink,et al.  Local structure of movement parallax of the plane , 1976 .

[5]  Hsieh Hou,et al.  Cubic splines for image interpolation and digital filtering , 1978 .

[6]  A.N. Netravali,et al.  Picture coding: A review , 1980, Proceedings of the IEEE.

[7]  H. C. Longuet-Higgins,et al.  The interpretation of a moving retinal image , 1980, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[8]  D Marr,et al.  Directional selectivity and its use in early visual processing , 1981, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[9]  John E. W. Mayhew,et al.  Psychophysical and Computational Studies Towards a Theory of Human Stereopsis , 1981, Artif. Intell..

[10]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[11]  D. Slepian.  Some comments on Fourier analysis, uncertainty and modeling , 1983 .

[12]  Edward H. Adelson,et al.  The Laplacian Pyramid as a Compact Image Code , 1983, IEEE Trans. Commun..

[13]  Dan E. Dudgeon,et al.  Multidimensional Digital Signal Processing , 1983 .

[14]  Hans-Hellmut Nagel,et al.  Displacement vectors derived from second-order intensity variations in image sequences , 1983, Comput. Vis. Graph. Image Process..

[15]  Hilary Buxton,et al.  Computation of optic flow from the motion of edge features in image sequences , 1984, Image Vis. Comput..

[16]  J. Daugman.  Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[17]  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.

[18]  A J Ahumada,et al.  Model of human visual-motion sensing. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[19]  Allen M. Waxman,et al.  Contour Evolution, Neighborhood Deformation, and Global Image Flow: Planar Surfaces in Motion , 1985 .

[20]  J. van Santen,et al.  Elaborated Reichardt detectors. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[21]  Hans-Hellmut Nagel,et al.  An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  F. Glazer.  Hierarchical Motion Detection , 1987 .

[23]  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.

[24]  James J. Little,et al.  Parallel Optical Flow Using Local Voting , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[25]  James H. Duncan,et al.  Temporal Edges: The Detection Of Motion And The Computation Of Optical Flow , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[26]  Wilfried Enkelmann,et al.  Investigations of multigrid algorithms for the estimation of optical flow fields in image sequences , 1988, Comput. Vis. Graph. Image Process..

[27]  Zenon W. Pylyshyn,et al.  Computational processes in human vision , 1988 .

[28]  J G Daugman,et al.  Pattern and motion vision without Laplacian zero crossings. , 1988, Journal of the Optical Society of America. A, Optics and image science.

[29]  Allen M. Waxman,et al.  Convected activation profiles and the measurement of visual motion , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[30]  Michael Jenkin,et al.  The Measurement of Binocular Disparity , 1988 .

[31]  David J. Fleet,et al.  Hierarchical Construction of Orientation and Velocity Selective Filters , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  R. Priemer.  FOURIER TRANSFORM AND APPLICATIONS , 1990 .

[33]  David J. Fleet.  Measurement of image velocity , 1992 .

[34]  T. Sanger,et al.  Stereo disparity computation using Gabor filters , 1988, Biological Cybernetics.

[35]  David J. Heeger,et al.  Optical flow using spatiotemporal filters , 2004, International Journal of Computer Vision.

[36]  P. Anandan,et al.  A computational framework and an algorithm for the measurement of visual motion , 1987, International Journal of Computer Vision.