Coalitional tracking

We propose a novel tracking method that uses a network of independent particle filter trackers whose interactions are modeled using coalitional game theory. Our tracking method is general, it maintains pixel level accuracy, and can negotiate surface deformations and occlusions. We tested our method on a substantial video set featuring non-trivial motion from over 40 objects in both the infrared and visual spectra. The coalitional tracker demonstrated fault tolerant behavior that exceeds by far the performance of single particle filter trackers. Our method represents a shift from the typical tracking paradigms and may find application in demanding imaging problems across the electromagnetic spectrum.

[1]  S.J. Krotosky,et al.  Face detection and head tracking using stereo and thermal infrared cameras for "smart" airbags: a comparative analysis , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[2]  Christian Schmidt,et al.  Game theory and economic analysis : a quiet revolution in economics , 2002 .

[3]  Shimon Ullman,et al.  Face Recognition: The Problem of Compensating for Changes in Illumination Direction , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Milan Mareš.  Fuzzy Cooperative Games , 2001 .

[5]  Lawrence B. Wolff,et al.  Tracking human faces in infrared video , 2003, Image Vis. Comput..

[6]  M. S. Burrell.  Computer vision for high-speed, high-volume manufacturing , 1993, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.

[7]  Anatol Rapoport,et al.  N-person game theory;: Concepts and applications , 1970 .

[8]  Ioannis Pavlidis,et al.  Urban surveillance systems: from the laboratory to the commercial world , 2001, Proc. IEEE.

[9]  T. Başar,et al.  Stochastic and differential games : theory and numerical methods , 1999 .

[10]  W. Clem Karl,et al.  Real-time tracking using level sets , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[11]  Wanda B. Mitchell,et al.  Chapter IV , 1958 .

[12]  Sergiu Hart,et al.  Cooperation: Game-Theoretic Approaches , 2012, NATO ASI Series.

[13]  Wolfgang Leiniger,et al.  Games and information: An introduction to game theory: Eric Rasmusen, (Basil Blackwell, Oxford, 1989) , 1991 .

[14]  James M. Rehg,et al.  Statistical Color Models with Application to Skin Detection , 2004, International Journal of Computer Vision.

[15]  Simon Baker,et al.  Equivalence and efficiency of image alignment algorithms , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[16]  Fadi Dornaika,et al.  Efficient active appearance model for real-time head and facial feature tracking , 2003, 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443).

[17]  Ying Wu,et al.  Decentralized multiple target tracking using netted collaborative autonomous trackers , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[18]  E. Rasmusen.  Games and Information: An Introduction to Game Theory , 2006 .

[19]  Ioannis Pavlidis,et al.  Seeing through the face of deception , 2002, Nature.

[20]  Timothy F. Cootes,et al.  Active Appearance Models , 1998, ECCV.

[21]  Anil K. Jain,et al.  Object Tracking Using Deformable Templates , 1998, ICCV.

[22]  Marc Garbey,et al.  Imaging the cardiovascular pulse , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[23]  Takeo Kanade,et al.  Algorithms for cooperative multisensor surveillance , 2001, Proc. IEEE.

[24]  Ioannis Pavlidis,et al.  The face of fear , 2001 .

[25]  Jean-Christophe Olivo-Marin,et al.  Coupled parametric active contours , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Andrew Blake,et al.  A Probabilistic Exclusion Principle for Tracking Multiple Objects , 2004, International Journal of Computer Vision.

[27]  Michael Isard,et al.  CONDENSATION—Conditional Density Propagation for Visual Tracking , 1998, International Journal of Computer Vision.

[28]  Michael Isard,et al.  BraMBLe: a Bayesian multiple-blob tracker , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[29]  Jin Fei,et al.  Imaging Breathing Rate in the CO2Absorption Band , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[30]  Rashid Ansari,et al.  Multiple object tracking with kernel particle filter , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[31]  M. A. Quintela,et al.  Defect assessment on radiant heaters using infrared thermography , 2005 .

[32]  Timothy J. Robinson,et al.  Sequential Monte Carlo Methods in Practice , 2003 .

[33]  Michael Isard,et al.  Partitioned Sampling, Articulated Objects, and Interface-Quality Hand Tracking , 2000, ECCV.

[34]  I. Pavlidis,et al.  Thermal image analysis for polygraph testing. , 2002, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[35]  Takahiro Ishikawa,et al.  The template update problem , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[36]  Marc Garbey,et al.  Estimation of blood flow speed and vessel location from thermal video , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[37]  Jorge Stolfi,et al.  Outlier Rejection in Deformable Model Tracking , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[38]  Ying Wu,et al.  Analyzing and capturing articulated hand motion in image sequences , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[39]  Timothy C. G. Fisher,et al.  Managerial Economics: A Game Theoretic Approach , 2002 .

[40]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[41]  P. Ekman,et al.  Lie Detection-Recovery of the Periorbital Signal through Tandem Tracking and Noise Suppression in Thermal Facial Video , 2005 .

[42]  Michael Isard,et al.  ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework , 1998, ECCV.

[43]  Ioannis Pavlidis,et al.  Human behaviour: Seeing through the face of deception , 2002, Nature.

[44]  Yacov Hel-Or,et al.  Constraint fusion for recognition and localization of articulated objects , 1996, International Journal of Computer Vision.