A simplified linear optic flow-motion algorithm

The purpose of the article is to establish the relationship between rigid body motion and the optic flow image and solve motion parameters from optic flow image points. A basic equation relating optic flow image points to rigid body motion which involves only the instantaneous rotation and translation velocities without depths is established. A linear algorithm is developed to determine the mode of motion (whether the instantaneous translation is zero or not), the instantaneous rotation velocity, the direction of the instantaneous translation velocity, and the relative depth map (or surface structure) under the rank assumption. The algorithm represents a simplification to the linear optic flow-motion algorithm proposed in ( Zhuang and Haralick , in Proceedings, IEEE First Conf. on Artificial Intelligence Applications, Denver, CO, 1984, pp. 366–375).

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

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

[3]  T S Huang,et al.  Two-view motion analysis: a unified algorithm. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[4]  Joseph K. Kearney,et al.  GRADIENT-BASED ESTIMATION OF OPTICAL FLOW WITH GLOBAL OPTIMIZATION. , 1984 .

[5]  Hans-Hellmut Nagel,et al.  Displacement vectors derived from second-order intensity variations in image sequences , 1983, Comput. Vis. Graph. Image Process..

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

[7]  A. Waxman.  An image flow paradigm , 1987 .

[8]  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.

[9]  J. H. Rieger,et al.  Determining the instantaneous axis of translation from optic flow generated by arbitrary sensot motion , 1986, Workshop on Motion.

[10]  H. C. Longuet-Higgins,et al.  A computer algorithm for reconstructing a scene from two projections , 1981, Nature.

[11]  R. Paquin,et al.  A spatio-temporal gradient method for estimating the displacement field in time-varying imagery , 1982, Computer Graphics and Image Processing.

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

[13]  K. Prazdny,et al.  On the information in optical flows , 1983, Comput. Vis. Graph. Image Process..

[14]  Xinhua Zhuang,et al.  A note on "Rigid body motion from depth and optical flow" , 1986, Comput. Vis. Graph. Image Process..

[15]  Jake K. Aggarwal,et al.  Dynamic scenes and object descriptions , 1982, ICASSP.

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

[17]  Shahriar Negahdaripour,et al.  Direct passive navigation: Analytical solution for planes , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[18]  Dana H. Ballard,et al.  Rigid body motion from depth and optical flow , 1983, Comput. Vis. Graph. Image Process..

[19]  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.

[20]  Kwang-Yun Wohn,et al.  Smoothing Optical Flow Fields , 1983 .

[21]  Ellen C. Hildreth,et al.  Measurement of Visual Motion , 1984 .

[22]  Ramesh C. Jain,et al.  Determining Motion Parameters for Scenes with Translation and Rotation , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  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.