Bayesian filtering for tracking pose and location of rigid targets

Tracking of target pose is important for ATR in situations where there is a relative motion between the targets and the sensor(s). Taking a Bayesian approach, we formulate the problem of jointly tracking the target positions and orientations as a problem in nonlinear filtering. Combining pertinent ideas form importance sampling and sequential methods, we apply an iterative Monte Carlo approach to solve for MMSE solutions. This tracking algorithm is demonstrated for tracking individual targets in a simulated environment.

[1]  M I Miller,et al.  Mathematical textbook of deformable neuroanatomies. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[2]  David Mumford,et al.  Statistics of natural images and models , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[3]  Olivier D. Faugeras,et al.  3D articulated models and multi-view tracking with silhouettes , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[4]  D HagerGregory,et al.  Efficient Region Tracking With Parametric Models of Geometry and Illumination , 1998 .

[5]  Michael Isard,et al.  Active Contours , 2000, Springer London.

[6]  Michael I. Miller,et al.  Hilbert-Schmidt Lower Bounds for Estimators on Matrix Lie Groups for ATR , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Ann B. Lee.  An Occlusion Model Generating Scale-Invariant Images , 1999 .

[8]  Takayuki Ito,et al.  A unified approach to video face detection, tracking and recognition , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[9]  U. Grenander,et al.  Asymptotic Performance Analysis of Bayesian Object Recognition , 1998 .

[10]  Patrick Bouthemy,et al.  Robust visual tracking by coupling 2D motion and 3D pose estimation , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[11]  R. White,et al.  Image recovery from data acquired with a charge-coupled-device camera. , 1993, Journal of the Optical Society of America. A, Optics and image science.

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

[13]  N. Gordon,et al.  Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .

[14]  J H Shapiro,et al.  Imaging and target detection with a heterodyne-reception optical radar. , 1981, Applied optics.

[15]  Jun S. Liu,et al.  Sequential Monte Carlo methods for dynamic systems , 1997 .