Active Gaze Control Improves Optic Flow-Based Segmentation and Steering

An observer traversing an environment actively relocates gaze to fixate objects. Evidence suggests that gaze is frequently directed toward the center of an object considered as target but more likely toward the edges of an object that appears as an obstacle. We suggest that this difference in gaze might be motivated by specific patterns of optic flow that are generated by either fixating the center or edge of an object. To support our suggestion we derive an analytical model that shows: Tangentially fixating the outer surface of an obstacle leads to strong flow discontinuities that can be used for flow-based segmentation. Fixation of the target center while gaze and heading are locked without head-, body-, or eye-rotations gives rise to a symmetric expansion flow with its center at the point being approached, which facilitates steering toward a target. We conclude that gaze control incorporates ecological constraints to improve the robustness of steering and collision avoidance by actively generating flows appropriate to solve the task.

[1]  Alan Yuille,et al.  Active Vision , 2014, Computer Vision, A Reference Guide.

[2]  Farhad Soleimanian Gharehchopogh,et al.  A Novel Approach for Edge Detection in Images Based on Cellular Learning Automata , 2012, Int. J. Comput. Vis. Image Process..

[3]  Nick Barnes,et al.  A Unified Strategy for Landing and Docking Using Spherical Flow Divergence , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  L. Itti,et al.  Mechanisms of top-down attention , 2011, Trends in Neurosciences.

[5]  Nicholas J. Butko,et al.  Active perception , 2010 .

[6]  Stephen Grossberg,et al.  A neural model of visually guided steering, obstacle avoidance, and route selection. , 2009, Journal of experimental psychology. Human perception and performance.

[7]  Constantin A Rothkopf,et al.  Image statistics at the point of gaze during human navigation , 2009, Visual Neuroscience.

[8]  Neumann Heiko.  Neural mechanisms of visual motion integration and ego-motion estimation - a modelling investigation , 2009 .

[9]  Richard Szeliski,et al.  A Database and Evaluation Methodology for Optical Flow , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[10]  Markus Lappe,et al.  Local statistics of retinal optic flow for self-motion through natural sceneries , 2007, Network.

[11]  Yiannis Aloimonos,et al.  A Probabilistic Framework for Correspondence and Egomotion , 2006, WDV.

[12]  Michael J. Black,et al.  On the Spatial Statistics of Optical Flow , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[13]  Steven C Dakin,et al.  An oblique effect for local motion: psychophysics and natural movie statistics. , 2005, Journal of vision.

[14]  D. Bradley,et al.  Structure and function of visual area MT. , 2005, Annual review of neuroscience.

[15]  Yiannis Aloimonos,et al.  Qualitative egomotion , 1995, International Journal of Computer Vision.

[16]  Yiannis Aloimonos,et al.  The role of fixation in visual motion analysis , 1993, International Journal of Computer Vision.

[17]  E. L. Schwartz,et al.  Spatial mapping in the primate sensory projection: Analytic structure and relevance to perception , 1977, Biological Cybernetics.

[18]  Thomas Brox,et al.  High Accuracy Optical Flow Estimation Based on a Theory for Warping , 2004, ECCV.

[19]  Berthold K. P. Horn.  Motion fields are hardly ever ambiguous , 1988, International Journal of Computer Vision.

[20]  Berthold K. P. Horn,et al.  Direct methods for recovering motion , 1988, International Journal of Computer Vision.

[21]  J. Koenderink,et al.  The singularities of the visual mapping , 1976, Biological Cybernetics.

[22]  Eric L. Schwartz,et al.  Stereo active vision and peripheral optical flow: computer vision applications of the wide-field human visual representation , 2004 .

[23]  Yiannis Aloimonos,et al.  Active vision , 2004, International Journal of Computer Vision.

[24]  R. Vautin,et al.  Magnification factor and receptive field size in foveal striate cortex of the monkey , 2004, Experimental Brain Research.

[25]  Brett R Fajen,et al.  Behavioral dynamics of steering, obstacle avoidance, and route selection. , 2003, Journal of experimental psychology. Human perception and performance.

[26]  Timo Kohlberger,et al.  Variational Dense Motion Estimation Using the Helmholtz Decomposition , 2003, Scale-Space.

[27]  Fabio Solari,et al.  Centric-minded templates for self-motion perception , 2003, Vision Research.

[28]  Jonathan R. Polimeni,et al.  The V1-V2-V3 complex: quasiconformal dipole maps in primate striate and extra-striate cortex , 2002, Neural Networks.

[29]  Yiannis Aloimonos,et al.  The Statistics of Optical Flow , 2001, Comput. Vis. Image Underst..

[30]  William H. Warren,et al.  Optic flow is used to control human walking , 2001, Nature Neuroscience.

[31]  David J. Fleet,et al.  Likelihood functions and confidence bounds for total-least-squares problems , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[32]  M. Hayhoe.  Vision Using Routines: A Functional Account of Vision , 2000 .

[33]  W. James MacLean.  Removal of translation bias when using subspace methods , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[34]  M. Land,et al.  The Roles of Vision and Eye Movements in the Control of Activities of Daily Living , 1998, Perception.

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

[36]  G. Orban,et al.  The spatial distribution of the antagonistic surround of MT/V5 neurons. , 1997, Cerebral cortex.

[37]  Constance S. Royden,et al.  Mathematical analysis of motion-opponent mechanisms used in the determination of heading and depth. , 1997, Journal of the Optical Society of America. A, Optics, image science, and vision.

[38]  James A. Crowell,et al.  Estimating heading during real and simulated eye movements , 1996, Vision Research.

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

[40]  R. Wurtz,et al.  Response of monkey MST neurons to optic flow stimuli with shifted centers of motion , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[41]  J. Perrone,et al.  A model of self-motion estimation within primate extrastriate visual cortex , 1994, Vision Research.

[42]  David N. Lee,et al.  Where we look when we steer , 1994, Nature.

[43]  Hans-Hellmut Nagel,et al.  Optical Flow Estimation: Advances and Comparisons , 1994, ECCV.

[44]  M. Graziano,et al.  Tuning of MST neurons to spiral motions , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[45]  O. Braddick.  Segmentation versus integration in visual motion processing , 1993, Trends in Neurosciences.

[46]  Markus Lappe,et al.  A Neural Network for the Processing of Optic Flow from Ego-Motion in Man and Higher Mammals , 1993, Neural Computation.

[47]  James A. Crowell,et al.  The perception of heading during eye movements , 1992, Nature.

[48]  A. V. D. Berg,et al.  Robustness of perception of heading from optic flow , 1992, Vision Research.

[49]  J J Bloomberg,et al.  The Effects of Target Distance on Eye and Head Movement during Locomotion , 1992, Annals of the New York Academy of Sciences.

[50]  J A Perrone,et al.  Model for the computation of self-motion in biological systems. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[51]  A. V. van den Berg.  Robustness of perception of heading from optic flow. , 1992, Vision research.

[52]  Eka Swadiansa.  The hypothesis , 1990 .

[53]  Yiannis Aloimonos,et al.  Obstacle Avoidance Using Flow Field Divergence , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[54]  Daniel J. Hannon,et al.  Direction of self-motion is perceived from optical flow , 1988, Nature.

[55]  W. Warren,et al.  Perception of translational heading from optical flow. , 1988, Journal of experimental psychology. Human perception and performance.

[56]  Allen M. Waxman,et al.  Binocular Image Flows: Steps Toward Stereo-Motion Fusion , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[57]  Gilad Adiv,et al.  Determining Three-Dimensional Motion and Structure from Optical Flow Generated by Several Moving Objects , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[58]  J H Rieger,et al.  Processing differential image motion. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[59]  Jan J. Koenderink,et al.  Space, Form and Optical Deformations , 1985 .

[60]  Eric L. Schwartz,et al.  Computational anatomy and functional architecture of striate cortex: A spatial mapping approach to perceptual coding , 1980, Vision Research.

[61]  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.

[62]  J. W. Humberston.  Classical mechanics , 1980, Nature.

[63]  J. Gibson.  The Ecological Approach to Visual Perception , 1979 .

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

[65]  K. Nakayama,et al.  Optical Velocity Patterns, Velocity-Sensitive Neurons, and Space Perception: A Hypothesis , 1974, Perception.

[66]  D A Gordon,et al.  Static and dynamic visul fields in human space perception. , 1965, Journal of the Optical Society of America.

[67]  Hermann von Helmholtz,et al.  Treatise on Physiological Optics , 1962 .

[68]  D. Whitteridge,et al.  The representation of the visual field on the cerebral cortex in monkeys , 1961, The Journal of physiology.

[69]  R. Hetherington.  The Perception of the Visual World , 1952 .