This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Effective Tracking through Tree-Search
May 2003 (vol. 25 no. 5)
pp. 604-615

Abstract—A new contour tracking algorithm is presented. Tracking is posed as a matching problem between curves constructed out of edges in the image, and some shape space describing the class of objects of interest. The main contributions of the paper are to present an algorithm which solves this problem accurately and efficiently, in a provable manner. In particular, the algorithm's efficiency derives from a novel tree-search algorithm through the shape space, which allows for much of the shape space to be explored with very little effort. This latter property makes the algorithm effective in highly cluttered scenes, as is demonstrated in an experimental comparison with a condensation tracker.

[1] YS. Akgul and C. Kambhamettu, “A Scale-Space Based Approach for Deformable Contour Optimization,” Scale-Space Theories in Computer Vision, pp. 410-422, Springer, 1999.
[2] A. Arsenio and J. Santos-Victor, “Robust Visual Tracking by an Active Observer,” Proc. 1997 IEEE/RSJ Int'l Conf. Intelligent Robot and Systems: Innovative Robotics for Real-World Applications, pp. 1342-1347, 1997.
[3] N. Ayache, I. Cohen, and I. Herlin, "Medical Image Tracking," Active Vision, chapter 17. MIT Press, Dec. 1992.
[4] A. Blake, Active Contours. Springer Verlag, 1998.
[5] A. Blake, R. Curwen, and A.A. Zisserman, “A Framework for Spatiotemporal Control in the Tracking of Visual Contours,” Int'l J. Computer Vision, vol. 11, no. 2, pp. 127-145, Oct. 1993.
[6] M. Isard and A. Blake, “Condensation-Conditional Density Propagation for Visual Tracking,” Int'l J. Computer Vision, vol. 29, pp. 5-28, 1998.
[7] A. Blake, M. Isard, and D. Reynard, “Learning to Track the Visual Motion of Contours,” Artificial Intelligence, no. 78, pp. 101-133, 1995.
[8] W. Boothby, An Introduction to Differentiable Manifolds and Riemannian Geometry. Second ed., Academic Press, 1986.
[9] C. Bregler and Y. Konig, “‘Eigenlips’for Robust Speech Recognition,” Proc. Int'l Conf. Acoustics, Speech, and Signal Processing, pp. 669-672, 1994.
[10] R. Brockett and A. Blake, “Estimating the Shape of a Moving Contour,” Proc. 33rd IEEE Conf. Decision and Control, pp. 3247-3252, 1994.
[11] V. Caselles, F. Catte, T. Coll, and F. Dibos, “A Geometric Model for Active Contours in Image Processing,” Numerical Math., vol. 66, pp. 1-31, 1993.
[12] V. Caselles, R. Kimmel, and G. Sapiro, “Geodesic Active Contours,” Int'l J. Computer Vision, vol. 22, no. 1, pp. 61-79, 1997.
[13] M. Chan, Y. Zhang, and T. Huang, “Real-Time Lip Tracking and Bimodal Continuous Speech Recognition,” Proc. 1998 IEEE Second Workshop Multimedia Signal Processing, pp. 65-70, 1998.
[14] B. Dalton, R. Kaucic, and A. Blake, “Automatic Speechreading Using Dynamic Contours,” Proc. NATO ASI Conf. Speechreading by Man and Machine: Models, Systems, and Applications, NATO Scientific Affairs Division, Sept. 1995.
[15] J. Dong, “Stable Snake Algorithm for Convex Tracking of MRI Sequences,” Electronics Letters, vol. 135, no. 13, pp. 1070-1071, 1999.
[16] L. Girin, E. Foucher, and G. Feng, “An Audio-Visual Distance for Audio-Visual Speech Vector Quantization,” Proc. 1998 IEEE Second Workshop Multimedia Signal Processing, pp. 523-528, 1998.
[17] L. Girin, G. Feng, and J. Schwartz, “Noisy Speech Enhancement by Fusion of Auditory and Visual Information: A Study of Vowel Transitions,” Proc. Fifth European Conf. Speech Comm. and Technology, pp. 2555-2558, 1997.
[18] A. Hill, A. Thornham, and C. Taylor, “Model Based Interpretation of 3D Medical Images,” Proc. Fourth British Machine Vision Conf., pp. 339-348, 1993.
[19] D. Hogg, “Model-Based Vision: A Program to See a Walking Person,” Image and Vision Computing, vol. 1, no. 1, pp. 5-20, 1983.
[20] M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active Contour Models,” Proc. First IEEE Int'l Conf. Computer Vision, June 1987.
[21] R. Kaucic and A. Blake, “Accurate, Real-Time, Unadorned Lip Tracking,” Proc. Sixth IEEE Int'l Conf. Computer Vision, pp. 370-375, 1998.
[22] R. Kaucic, B. Dalton, and A. Blake, “Real-Time Lip Tracking for Audio-Visual Speech Recognition Applications,” Proc. European Conf. Computer Vision, B. Buxton and R. Cipolla, eds., pp. 376-387, Apr. 1996.
[23] D. Koller, J. Weber, and J. Malik, “Towards Realtime Visual Based Tracking in Cluttered Traffic Scenes,” Proc. Intelligent Vehicles '94 Symp., pp. 201-206, 1994.
[24] M. Lievin, P. Delmas, P. Coulon, F. Luthon, and V. Fristol, “Automatic Lip Tracking: Bayesian Segmentation and Active Contours in a Cooperative Scheme,” Proc. IEEE Int'l Conf. Multimedia Computing and Systems, pp. 691-696, 1999.
[25] P. Lipson, A. Yuille, D. O'Keefe, J. Cavanaugh, J. Taafe, and D. Rosenthal, “Deformable Templates for Feature Extraction from Medical Images,” Proc. First European Conf. Computer Vision, 1990.
[26] J. Luettin, N. Thacker, and S. Beet, “Visual Speech Recognition Using Active Shape Models and Hidden Markov Models,” Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing, pp. 817-820, 1996.
[27] S. McKenna and S. Gong, “Tracking Faces,” Proc. Second Int'l Conf. Automatic Face and Gesture Recognition, pp. 271-276, 1996.
[28] M. Mignotte and J. Meunier, “Deformable Template and Distribution Mixture-Based Data Modeling for the Endocardial Contour Tracking in an Echographic Sequence,” Proc. 1999 IEEE Computer Soc. Conf. Computer Vision and Pattern Recognition, pp. 225-230, 1999.
[29] J. Munkres, Topology: A First Course. Prentice-Hall, 1975.
[30] B. Rao, H. Durrant-Whyte, and J. Sheen, “A Fully Decentralized Multi-Sensor System for Tracking and Surveillance,” Int'l J. Robotics Research, vol. 12, no. 1, pp. 20-44, 1993.
[31] J. Sanchiz, F. Pla, and J. Marchant, “Vision-Based Approach to Automate Spraying in Crop Fields,” Proc. SPIE—The Int'l Soc. for Optical Eng., vol. 3364, pp. 287-297, 1998.
[32] I. Schwartz, “Primus. Realization Aspects of an Autonomous Unmanned Robot,” Proc. SPIE—The Int'l Soc. for Optical Eng., vol. 3364, pp. 328-334, 1998.
[33] G. Sullivan, “Visual Interpretation of Known Objects in Constrained Scenes,” Philosophical Trans. Royal Soc. of London B, vol. 337, pp. 109-118, 1992.
[34] F. Thomanek, E. Dickmanns, and D. Dickmanns, “Multiple Object Recognition and Scene Interpretation for Autonomous Road Vehicle Guidance,” Proc. Intelligent Vehicles '94 Symp., pp. 231-236, 1994.
[35] G. Xu, E. Segawa, and S. Tsuji, “Robust Active Contours with Insensitive Parameters,” Proc. Fourth IEEE Int'l Conf. Computer Vision, May 1993.
[36] A.L. Yuille, P.W. Hallinan, and D.S. Cohen, "Feature extraction from faces using deformable templates," Int'l J. Computer Vision, vol. 8, no. 2, 133-144, 1992.

Index Terms:
Contour tracking, tree-search, hybrid optimization, approximation algorithm, compact manifold.
Citation:
Daniel Freedman, "Effective Tracking through Tree-Search," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 5, pp. 604-615, May 2003, doi:10.1109/TPAMI.2003.1195994
Usage of this product signifies your acceptance of the Terms of Use.