Motion Stereo Using Ego-Motion Complex Logarithmic Mapping

Stereo information can be obtained using a moving camera. If a dynamic scene is acquired using a translating camera and the camera motion parameters are known, then the analysis of the scene may be facilitated by ego-motion complex logarithmic mapping (ECLM). It is shown in this paper that by using the complex logarithmic mapping (CLM) with respect to the focus of expansion, the depth of stationary components can be determined easily in the transformed image sequence. The proposed approach for depth recovery avoids the difficult problems of establishing correspondence and computation of optical flow, by using the ego-motion information. An added advantage of the CLM will be the invariances it offers. We report our experiments with synthetic data to show the sensitivity of the depth recovery, and show results of real scenes to demonstrate the efficacy of the proposed motion stereo in applications such as autonomous navigation.

[1]  W. Eric L. Grimson,et al.  Binocular shading and visual surface reconstruction , 1984, Comput. Vis. Graph. Image Process..

[2]  E. Schwartz.  The development of specific visual connections in the monkey and the goldfish: outline of a geometric theory of receptotopic structure. , 1977, Journal of theoretical biology.

[3]  Giulio Sandini,et al.  An anthropomorphic retina-like structure for scene analysis , 1980 .

[4]  Ramakant Nevatia,et al.  Depth measurement by motion stereo , 1976 .

[5]  Eric L. W. Grimson,et al.  From Images to Surfaces: A Computational Study of the Human Early Visual System , 1981 .

[6]  Chengke Wu,et al.  Acquiring 3-D spatial data of a real object , 1984, Comput. Vis. Graph. Image Process..

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

[8]  Anthony P. Reeves,et al.  Three-Dimensional Shape Analysis Using Moments and Fourier Descriptors , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

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

[10]  S. Ullman.  The Interpretation of Visual Motion , 1979 .

[11]  Greg L. Zacharias,et al.  A visual cueing model for terrain-following applications , 1983 .

[12]  Charles E. Thorpe,et al.  Experience with Visual Robot Navigation , 1984 .

[13]  Greg L. Zacharias,et al.  A Model for Visual Flow-Field Cueing and Self-Motion Estimation , 1983, 1983 American Control Conference.

[14]  Lee Dn,et al.  The optic flow field: the foundation of vision. , 1980 .

[15]  Thomas S. Huang,et al.  MATCHING PERSPECTIVE VIEWS OF A 3-D OBJECT USING CIRCUITS. , 1984 .

[16]  P. Cavanagh.  Size Invariance: Reply to Schwartz , 1981, Perception.

[17]  P Cavanagh,et al.  Size and Position Invariance in the Visual System , 1978, Perception.

[18]  Martin A. Fischler,et al.  Computational Stereo , 1982, CSUR.

[19]  Ramesh Jain,et al.  Axial motion stereo , 1984 .

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

[21]  Hans P. Moravec.  Robot Rover Visual Navigation , 1981 .

[22]  E L Schwartz,et al.  Cortical Anatomy, Size Invariance, and Spatial Frequency Analysis , 1981, Perception.

[23]  Ramesh Jain,et al.  Ego-Motion Complex Logarithmic Mapping , 1985, Other Conferences.

[24]  Ramesh C. Jain,et al.  Segmentation of Frame Sequences Obtained by a Moving Observer , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  P. S. Schenker,et al.  Fast Adaptive Algorithms For Low-Level Scene Analysis: Applications Of Polar Exponential Grid (PEG) Representation To High-Speed, Scale-And-Rotation Invariant Target Segmentation , 1981, Other Conferences.

[26]  R. J. Safranek,et al.  Stereoscopic depth perception for robot vision: algorithms and architectures , 1983 .

[27]  Giulio Sandini,et al.  "Form-invariant" topological mapping strategy for 2D shape recognition , 1985, Comput. Vis. Graph. Image Process..

[28]  H. K. Nishihara,et al.  Practical Real-Time Imaging Stereo Matcher , 1984 .

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

[30]  Richard A. Messner,et al.  An image processing architecture for real time generation of scale and rotation invariant patterns , 1985, Comput. Vis. Graph. Image Process..

[31]  Henri H. Arsenault,et al.  Rotation-Invariant Pattern Recognition , 1984 .

[32]  Berthold K. P. Horn,et al.  Passive navigation , 1982, Computer Vision Graphics and Image Processing.