Tracking a dynamic set of feature points

We address the problems of tracking a set of feature points over a long sequence of monocular images as well as how to include and track new feature points detected in successive frames. Due to the 3-D movement of the camera, different parts of the images exhibit different image motion. Tracking discrete features can therefore be decomposed into several independent and local problems. Accordingly, we propose a localized feature tracking algorithm. The trajectory of each feature point is described by a 2-D kinematic model. Then to track a feature point, an interframe motion estimation scheme is designed to obtain the estimates of interframe motion parameters. Subsequently, using the estimates of motion parameters, corresponding points are identified to subpixel accuracy. Afterwards, the temporal information is processed to facilitate the tracking scheme. Since different feature points are tracked independently, the algorithm is able to handle the image motion arising from general 3-D camera movements. On the other hand, in addition to tracking feature points detected at the beginning, an efficient way to dynamically include new points extracted in subsequent frames is devised so that the information in a sequence is preserved. Experimental results for several image sequences are also reported.

[1]  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..

[2]  Narendra Ahuja,et al.  Matching Two Perspective Views , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Steven D. Blostein,et al.  Detecting small, moving objects in image sequences using sequential hypothesis testing , 1991, IEEE Trans. Signal Process..

[4]  Ishwar K. Sethi,et al.  Finding Trajectories of Feature Points in a Monocular Image Sequence , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Peter E. Hart,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[6]  George Wolberg,et al.  Digital image warping , 1990 .

[7]  Y. Bar-Shalom.  Tracking and data association , 1988 .

[8]  Gösta H. Granlund,et al.  Image Sequence Analysis , 1993, DAGM-Symposium.

[9]  Rama Chellappa,et al.  Time-to-X: analysis of motion through temporal parameters , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[10]  Lisa M. Brown,et al.  A survey of image registration techniques , 1992, CSUR.

[11]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[12]  Jake K. Aggarwal,et al.  MOTION AND TIME - VARYING IMAGERY - AN OVERVIEW. , 1986 .

[13]  Rama Chellappa,et al.  A feature based approach to face recognition , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[14]  Rama Chellappa,et al.  Estimating the Kinematics and Structure of a Rigid Object from a Sequence of Monocular Images , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

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

[16]  Paul R. Cohen,et al.  Extended structure and motion analysis from monocular image sequences , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[17]  Steven D. Blostein,et al.  MOTION DETECTION AND ESTIMATION FROM STEREO IMAGE SEQUENCES: SOME PRELIMINARY EXPERIMENTAL RESULTS. , 1986 .

[18]  J. K. Aggarwal,et al.  3D structure reconstruction from an ego motion sequence using statistical estimation and detection theory , 1991, Proceedings of the IEEE Workshop on Visual Motion.

[19]  Yaakov Bar-Shalom,et al.  Tracking methods in a multitarget environment , 1978 .

[20]  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.