3-d motion Analysis from Image sequences using Point Correspondences

The objective is to analyze the motion between a rigid scene and the camera. The temporal correspondences between consecutive images are established by a procedure of image matching. Such temporal correspondences are then used for the estimation of the three-dimensional (3-D) interframe motions, as well as the 3-D structure of the scene. Long term motion that covers many image frames is modeled using object dynamics, and the model parameters are determined from the interframe motions. Thus, smooth 3-D motion can be predicted using the model parameters.

[1]  John E. W. Mayhew,et al.  Psychophysical and Computational Studies Towards a Theory of Human Stereopsis , 1981, Artif. Intell..

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

[3]  Ramesh C. Jain,et al.  On the Analysis of Accumulative Difference Pictures from Image Sequences of Real World Scenes , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  J. Y. Yang,et al.  Matching Perspective Views of a Polyhedron Using Circuits , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Joseph K. Kearney,et al.  Optical Flow Estimation: An Error Analysis of Gradient-Based Methods with Local Optimization , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Paul R. Cohen,et al.  Motion and structure estimation from stereo image sequences , 1992, IEEE Trans. Robotics Autom..

[7]  A.D. Jepson,et al.  The fast computation of disparity from phase differences , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

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

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

[10]  Jake K. Aggarwal,et al.  A computational analysis of time-varying images. , 1986 .

[11]  Rama Chellappa,et al.  3-D Motion Estimation Using a Sequence of Noisy Stereo Images: Models, Estimation, and Uniqueness Results , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Hans-Hellmut Nagel,et al.  An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Narendra Ahuja,et al.  Two-view Matching , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[14]  Thomas S. Huang,et al.  Some Experiments on Estimating the 3-D Motion Parameters of a Rigid Body from Two Consecutive Image Frames , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

[16]  Narendra Ahuja,et al.  Motion and Structure From Two Perspective Views: Algorithms, Error Analysis, and Error Estimation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  David J. Heeger,et al.  Optical flow using spatiotemporal filters , 2004, International Journal of Computer Vision.

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

[19]  Narendra Ahuja,et al.  3-D Motion Estimation, Understanding, and Prediction from Noisy Image Sequences , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  F. Glazer,et al.  Scene Matching by Hierarchical Correlation , 1983 .

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

[22]  Tomaso Poggio,et al.  A Theory of Human Stereo Vision , 1977 .

[23]  Juyang Weng,et al.  A theory of image matching , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[24]  Takeo Kanade,et al.  Stereo by Intra- and Inter-Scanline Search Using Dynamic Programming , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  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.

[26]  Ernest L. Hall,et al.  Matching of featured objects using relational tables from stereo images , 1982, Comput. Graph. Image Process..