The Ouchi illusion as an artifact of biased flow estimation

A pattern by Ouchi has the surprising property that small motions can cause illusory relative motion between the inset and background regions. The effect can be attained with small retinal motions or a slight jiggling of the paper and is robust over large changes in the patterns, frequencies and boundary shapes. In this paper, we explain that the cause of the illusion lies in the statistical difficulty of integrating local one-dimensional motion signals into two-dimensional image velocity measurements. The estimation of image velocity generally is biased, and for the particular spatial gradient distributions of the Ouchi pattern the bias is highly pronounced, giving rise to a large difference in the velocity estimates in the two regions. The computational model introduced to describe the statistical estimation of image velocity also accounts for the findings of psychophysical studies with variations of the Ouchi pattern and for various findings on the perception of moving plaids. The insight gained from this computational study challenges the current models used to explain biological vision systems and to construct robotic vision systems. Considering the statistical difficulties in image velocity estimation in conjunction with the problem of discontinuity detection in motion fields suggests that theoretically the process of optical flow computations should not be carried out in isolation but in conjunction with the higher level processes of 3D motion estimation, segmentation and shape computation.

[1]  B. Khang,et al.  Apparent Relative Motion from a Checkerboard Surround , 1997, Perception.

[2]  Kostas Daniilidis,et al.  Understanding noise sensitivity in structure from motion , 1996 .

[3]  D. H. Kelly Motion and vision. II. Stabilized spatio-temporal threshold surface. , 1979, Journal of the Optical Society of America.

[4]  P. Wenderoth,et al.  The effect of interactions between one-dimensional component gratings on two-dimensional motion perception , 1993, Vision Research.

[5]  Y. Aloimonos,et al.  Direct Perception of Three-Dimensional Motion from Patterns of Visual Motion , 1995, Science.

[6]  Ellen C. Hildreth,et al.  Computations Underlying the Measurement of Visual Motion , 1984, Artif. Intell..

[7]  Ramesh C. Jain,et al.  Segmentation through Variable-Order Surface Fitting , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  R. Wurtz,et al.  Sensitivity of MST neurons to optic flow stimuli. I. A continuum of response selectivity to large-field stimuli. , 1991, Journal of neurophysiology.

[9]  Berthold K. P. Horn Robot vision , 1986, MIT electrical engineering and computer science series.

[10]  D. Hubel,et al.  Receptive fields and functional architecture of monkey striate cortex , 1968, The Journal of physiology.

[11]  K. Nakayama,et al.  The aperture problem—II. Spatial integration of velocity information along contours , 1988, Vision Research.

[12]  W. Kiel,et al.  Direct Perception of Three-Dimensional Motion from Patterns of Visual Motion , 1995 .

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

[14]  S Zeki,et al.  Going beyond the information given: the relation of illusory visual motion to brain activity , 1993, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[15]  Kostas Daniilidis,et al.  Fixation Simplifies 3D Motion Estimation , 1997, Comput. Vis. Image Underst..

[16]  Vincent P. Ferrera,et al.  Perceived speed of moving two-dimensional patterns , 1991, Vision Research.

[17]  D. Shulman,et al.  Regularization of discontinuous flow fields , 1989, [1989] Proceedings. Workshop on Visual Motion.

[18]  D C Van Essen,et al.  Functional properties of neurons in middle temporal visual area of the macaque monkey. I. Selectivity for stimulus direction, speed, and orientation. , 1983, Journal of neurophysiology.

[19]  Loong Fah Cheong,et al.  Visual space distortion , 1997, Biological Cybernetics.

[20]  Trevor J. Hine,et al.  An illusion of relative motion dependent upon spatial frequency and orientation , 1995, Vision Research.

[21]  Lawrence Stark,et al.  Neurological Control Systems: Studies in Bioengineering , 1995 .

[22]  Vishal Markandey,et al.  Total least squares fitting spatiotemporal derivatives to smooth optical flow fields , 1992, Defense, Security, and Sensing.

[23]  S. Zeki Functional organization of a visual area in the posterior bank of the superior temporal sulcus of the rhesus monkey , 1974, The Journal of physiology.

[24]  Yiannis Aloimonos,et al.  Representations for Active Vision , 1995, IJCAI.

[25]  Olivier Faugeras,et al.  Three-Dimensional Computer Vision , 1993 .

[26]  Y. Aloimonos,et al.  Families of stationary patterns producing illusory movement: insights into the visual system , 1997, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[27]  John H. R. Maunsell,et al.  Functional properties of neurons in middle temporal visual area of the macaque monkey. II. Binocular interactions and sensitivity to binocular disparity. , 1983, Journal of neurophysiology.

[28]  Hans Wallach Über visuell wahrgenommene Bewegungsrichtung , 1935 .

[29]  T. Hine,et al.  The Ouchi illusion: An anomaly in the perception of rigid motion for limited spatial frequencies and angles , 1997, Perception & psychophysics.

[30]  H. Wilson,et al.  Moving two-dimensional patterns can capture the perceived directions of lower or higher spatial frequency gratings , 1992, Vision Research.

[31]  Vincent P. Ferrera,et al.  Direction specific masking and the analysis of motion in two dimensions , 1987, Vision Research.

[32]  Hans-Hellmut Nagel,et al.  Bias-corrected optical flow estimation for road vehicle tracking , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[33]  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.

[34]  T. D. Albright,et al.  Transparency and coherence in human motion perception , 1990, Nature.

[35]  E. Adelson,et al.  The analysis of moving visual patterns , 1985 .

[36]  B. Khang,et al.  A Motion Illusion from Two-Dimensional Periodic Patterns , 1997, Perception.

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

[38]  Ja Movshon,et al.  Visual processing of moving images , 1990 .

[39]  Leslie Welch,et al.  The perception of moving plaids reveals two motion-processing stages , 1989, Nature.

[40]  A. Rosenfeld,et al.  Perceptual motion transparency : the role of geometrical information , 1992 .

[41]  Vision Research , 1961, Nature.

[42]  Frank L. Kooi,et al.  Properties of the recombination of one-dimensional motion signals into a pattern motion signal , 1992, Perception & psychophysics.

[43]  R. Wurtz,et al.  Sensitivity of MST neurons to optic flow stimuli. II. Mechanisms of response selectivity revealed by small-field stimuli. , 1991, Journal of neurophysiology.

[44]  A. T. Smith,et al.  Perceived speed and direction of complex gratings and plaids. , 1991, Journal of the Optical Society of America. A, Optics and image science.

[45]  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.

[46]  Edward H. Adelson,et al.  Probability distributions of optical flow , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[47]  Jeounghoon Kim,et al.  Dependence of plaid motion coherence on component grating directions , 1993, Vision Research.

[48]  K. Nakayama,et al.  The aperture problem—I. Perception of nonrigidity and motion direction in translating sinusoidal lines , 1988, Vision Research.

[49]  Guy A. Orban,et al.  The Analysis of Motion Signals and the Nature of Processing in the Primate Visual System , 1992 .

[50]  R. L. Valois,et al.  The orientation and direction selectivity of cells in macaque visual cortex , 1982, Vision Research.

[51]  Yiannis Aloimonos Visual Navigation: From Biological Systems to Unmanned Ground Vehicles , 1996 .

[52]  Leslie G. Ungerleider,et al.  Cortical connections of visual area MT in the macaque , 1986, The Journal of comparative neurology.

[53]  Stephen M. Smith,et al.  ASSET-2: real-time motion segmentation and shape tracking , 1995, Proceedings of IEEE International Conference on Computer Vision.