Maximizing Rigidity: The Incremental Recovery of 3-D Structure from Rigid and Nonrigid Motion

The human visual system can extract 3-D shape information of unfamiliar moving objects from their projected transformations. Computational studies of this capacity have established that 3-D shape can be extracted correctly from a brief presentation, provided the moving objects are rigid. The human visual system requires a longer temporal extension, but it can cope with considerable deviations from rigidity. It is shown how the 3-D structure of rigid as well as nonrigid objects can be recovered by maintaining an internal model of the viewed object and modifying it at each instant by the minimal nonrigid change that is sufficient to account for the observed transformation. The results of applying this incremental rigidity scheme to rigid and nonrigid objects in motion are described and compared with human perception.

[1]  W. Miles Movement Interpretations of the Silhouette of a Revolving Fan , 1931 .

[2]  H. Wallach,et al.  The memory effect of visual perception of three-dimensional form. , 1953, Journal of experimental psychology.

[3]  H. Wallach,et al.  Circles and derived figures in rotation. , 1956, The American journal of psychology.

[4]  J. Gibson,et al.  Continuous perspective transformations and the perception of rigid motion. , 1957, Journal of experimental psychology.

[5]  G. E. Mueser,et al.  Accuracy in reconstructing the arrangement of elements generating kinetic depth displays. , 1960, Journal of experimental psychology.

[6]  Green Bf Figure coherence in the kinetic depth effect. , 1961 .

[7]  B. Green Figure coherence in the kinetic depth effect. , 1961, Journal of experimental psychology.

[8]  M. Braunstein Depth perception in rotating dot patterns: effects of numerosity and perspective. , 1962, Journal of experimental psychology.

[9]  G. Johansson PERCEPTION OF MOTION AND CHANGING FORM: A study of visual perception from continuous transformations of a solid angle of light at the eye , 1964 .

[10]  J. Hay,et al.  Optical motions and space perception: an extension of Gibson's analysis. , 1966, Psychological review.

[11]  Gunnar Johansson,et al.  Perceived rotary motion from changes in a straight line , 1968 .

[12]  William C. Davidon,et al.  Variance Algorithm for Minimization , 1968, Comput. J..

[13]  R. Shepard,et al.  Mental Rotation of Three-Dimensional Objects , 1971, Science.

[14]  G. Johansson,et al.  Visual Perception of Bending Motion , 1973, Perception.

[15]  O. Braddick A short-range process in apparent motion. , 1974, Vision research.

[16]  Andrea J. van Doorn,et al.  Invariant Properties of the Motion Parallax Field due to the Movement of Rigid Bodies Relative to an Observer , 1975 .

[17]  David N. Lee,et al.  A Theory of Visual Control of Braking Based on Information about Time-to-Collision , 1976, Perception.

[18]  M. Braunstein Depth perception through motion , 1976 .

[19]  Gunnar Johansson,et al.  Visual Event Perception , 1978 .

[20]  J T Petersik,et al.  Three-dimensional object constancy: Coherence of a simulated rotating sphere in noise , 1979, Perception & psychophysics.

[21]  Shimon Ullman,et al.  Relaxation and constrained optimization by local processes , 1979 .

[22]  Claude L. Fennema,et al.  Velocity determination in scenes containing several moving objects , 1979 .

[23]  S. Ullman The interpretation of structure from motion , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[24]  D. N. Lee The optic flow field: the foundation of vision. , 1980, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[25]  W F Clocksin,et al.  Perception of Surface Slant and Edge Labels from Optical Flow: A Computational Approach , 1980, Perception.

[26]  J S Lappin,et al.  Minimal conditions for the visual detection of structure and motion in three dimensions. , 1980, Science.

[27]  J. T. Petersik,et al.  The Effects of Spatial and Temporal Factors on the Perception of Stroboscopic Rotation Simulations , 1980, Perception.

[28]  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.

[29]  Jake K. Aggarwal,et al.  Visually Interpreting the Motion of Objects in Space , 1981, Computer.

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

[31]  H. C. Longuet-Higgins The Role of the Vertical Dimension in Stereoscopic Vision , 1982, Perception.

[32]  E. Adelson,et al.  Phenomenal coherence of moving visual patterns , 1982, Nature.

[33]  S. Ullman The measurement of visual motion Computational considerations and some neurophysiological implications , 1983, Trends in Neurosciences.

[34]  Andrew C. Sleigh,et al.  Physical and Biological Processing of Images , 1983 .

[35]  E. Ingelstam Physical and Biological Processing of Images , 1983 .

[36]  J S Lappin,et al.  Accurate visual measurement of three-dimensional moving patterns. , 1983, Science.

[37]  S. Ullman Recent Computational Studies in the Interpretation of Structure from Motion , 1983 .

[38]  Thomas S. Huang,et al.  Uniqueness and Estimation of Three-Dimensional Motion Parameters of Rigid Objects with Curved Surfaces , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[39]  Aaron Bobick A hybrid approach to structure-from-motion , 1986, SIGGRAPH 1986.