Processing translational motion sequences

Abstract A procedure for processing real world image sequences produced by relative translational motion between a sensor and environmental objects is presented. In this procedure, the determination of the direction of sensor translation is effectively combined with the determination of the displacement of image features and environmental depth. It requires no restrictions on the direction of motion, nor the location and shape of environmental objects. It has been applied successfully to real-world image sequences from several different task domains. The processing consists of two basic steps: feature extraction and search. The feature extraction process picks out small image areas which may correspond to distinguishing parts of environmental objects. The direction of translational motion is then found by a search which determines the image displacement paths along which a measure of feature mismatch is minimized for a set of features. The correct direction of translation will minimize this error measure and also determine the corresponding image displacement paths for which the extracted features match well.

[1]  John K. Tsotsos,et al.  A framework for visual motion understanding , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  John Martin Prager,et al.  Segmentation of static and dynamic scenes. , 1979 .

[3]  Daryl T Lawton.  Motion Analysis via Local Translational Processing. , 1982 .

[4]  J. O'Rourke,et al.  Model-based image analysis of human motion using constraint propagation , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  L. Quam.  Computer comparison of pictures , 1971 .

[6]  John R. Kender,et al.  Shape from Texture: An Aggregation Transform that Maps a Class of Textures into Surface Orientation , 1979, IJCAI.

[7]  Martin D. Levine,et al.  Computer determination of depth maps , 1973, Comput. Graph. Image Process..

[8]  Azriel Rosenfeld,et al.  Threshold Selection Techniques, 5. , 1975 .

[9]  Thomas S. Huang,et al.  Estimating three-dimensional motion parameters of a rigid planar patch , 1981 .

[10]  K. Prazdny,et al.  Determining The Instantaneous Direction Of Motion From Optical Flow Generated By A Curvilinearly Moving Observer , 1981, Other Conferences.

[11]  Paul Alexander Nagin.  Studies in image segmentation algorithms based on histogram clustering and relaxation , 1979 .

[12]  John B. Goodenough.  The Ada Compiler Validation Capability , 1981 .

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

[14]  Frank Glazer.  Computing optic flow , 1981, IJCAI 1981.

[15]  M. Cynader,et al.  Stereoscopic subsystems for position in depth and for motion in depth , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[16]  R. Woodham,et al.  Determining the movement of objects from a sequence of images , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  J. Gibson.  The Senses Considered As Perceptual Systems , 1967 .

[18]  Gilad Adiv.  Recovering 2-D Motion Parameters in Scenes Containing Multiple Moving Objects. , 1983 .

[19]  Hans P. Moravec.  Rover Visual Obstacle Avoidance , 1981, IJCAI.

[20]  W. B. Thompson,et al.  Combining motion and contrast for segmentation , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

[22]  William B. Thompson,et al.  Lower-Level Estimation and Interpretation of Visual Motion , 1981, Computer.

[23]  T. D. Williams,et al.  Depth from camera motion in a real world scene , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  B. M. Radig,et al.  Image Region Extraction of Moving Objects , 1981 .

[25]  Shimon Ullman,et al.  Analysis of Visual Motion by Biological and Computer Systems , 1981, Computer.

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

[27]  Ramesh C. Jain,et al.  Extraction of Motion Information from Peripheral Processes , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  J. Gibson.  The perception of the visual world , 1951 .

[29]  Hans P. Morevec.  Towards automatic visual obstacle avoidance , 1977, IJCAI 1977.

[30]  Marsha Jo Hannah,et al.  Computer matching of areas in stereo images. , 1974 .

[31]  H. H. Nagel,et al.  Image Sequence Analysis: What Can We Learn from Applications? , 1981 .

[32]  S. Ullman,et al.  The interpretation of visual motion , 1977 .

[33]  R. Kohler.  A segmentation system based on thresholding , 1981 .

[34]  William B. Thompson,et al.  Disparity Analysis of Images , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  Ellen C. Hildreth,et al.  Implementation Of A Theory Of Edge Detection , 1980 .

[36]  D. Regan,et al.  Looming detectors in the human visual pathway , 1978, Vision Research.

[37]  Norman I. Badler,et al.  Temporal scene analysis: conceptual descriptions of object movements. , 1975 .

[38]  Jake K. Aggarwal,et al.  Computer analysis of dynamic scenes containing curvilinear figures , 1979, Pattern Recognit..

[39]  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.

[40]  Dana H. Ballard,et al.  Parameter Networks: Towards a Theory of Low-Level Vision , 1981, IJCAI.

[41]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[42]  Hans-Hellmut Nagel,et al.  Formation of an object concept by analysis of systematic time variations in the optically perceptible environment , 1978 .