A Robust Tracking of 3D Motion

The tracking of moving objects in the 3D space for long-term image sequences must be very robust with respect to noise and computational errors. Thus, for example autoregressive, and Newtonian models have been adopted mainly with least-square, Kalman filter, and other techniques. The parameters measured are predicted/corrected on the basis of the model adopted; which can be adaptive or not. In this paper, a new method for tracking objects in the 3D space belonging to the class of matching-based algorithms with an adaptive prediction/correction mechanism is presented. The prediction/correction is based on 2D and 3D motion estimations, and both these corrections are used for measuring the displacements on the image plane. The mechanism proposed is very robust with respect to the accumulation error and, thus, it is suitable for very long-term object tracking.

[1]  Alberto Del Bimbo,et al.  Behavioral object recognition from multiple image frames , 1992, Signal Process..

[2]  Reinhard Koch,et al.  Dynamic 3-D Scene Analysis Through Synthesis Feedback Control , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  R. Chellappa,et al.  Experiments and uniqueness results on object structure and kinematics from a sequence of monocular images , 1989, [1989] Proceedings. Workshop on Visual Motion.

[4]  Pertti Roivainen,et al.  3-D Motion Estimation in Model-Based Facial Image Coding , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

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

[6]  Robert Forchheimer,et al.  Image coding-from waveforms in animation , 1989, IEEE Trans. Acoust. Speech Signal Process..

[7]  Hormoz Shariat,et al.  Motion Estimation with More than Two Frames , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Demetri Terzopoulos,et al.  Analysis and Synthesis of Facial Image Sequences Using Physical and Anatomical Models , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Alberto Del Bimbo,et al.  Optical flow from constraint lines parametrization , 1993, Pattern Recognit..

[10]  P. Pirsch,et al.  Advances in picture coding , 1985, Proceedings of the IEEE.

[11]  Paolo Nesi,et al.  Variational approach to optical flow estimation managing discontinuities , 1993, Image Vis. Comput..

[12]  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.