Fast texture-based tracking and delineation using texture entropy

We propose a fast texture-segmentation approach to the problem of 2D and 3D model-based contour tracking, which is suitable for real-time or interactive applications. Our approach relies on detecting texture boundaries in the direction normal to the contour boundaries and on using a hidden Markov model to link these boundary points in the other direction. The probabilities that appear in this computation closely relate to texture entropy and Kullback-Leibler divergence, a property we use to compute and update dynamic texture models. We demonstrate results both in the context of interactive 2D delineation and fast 3D tracking

[1]  Stan Sclaroff,et al.  Estimating 3D hand pose from a cluttered image , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[2]  Patrick Pérez,et al.  Interactive Image Segmentation Using an Adaptive GMMRF Model , 2004, ECCV.

[3]  Nuno Vasconcelos,et al.  The Kullback-Leibler Kernel as a Framework for Discriminant and Localized Representations for Visual Recognition , 2004, ECCV.

[4]  Jitendra Malik,et al.  A real-time approach to stereopsis and lane-finding , 1996, Proceedings of Conference on Intelligent Vehicles.

[5]  B. Triggs,et al.  3D human pose from silhouettes by relevance vector regression , 2004, CVPR 2004.

[6]  Jr. G. Forney,et al.  The viterbi algorithm , 1973 .

[7]  Rajeev Sharma,et al.  Adaptive texture and color segmentation for tracking moving objects , 2002, Pattern Recognit..

[8]  Roberto Cipolla,et al.  Real-Time Visual Tracking of Complex Structures , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Andrew Blake,et al.  "GrabCut" , 2004, ACM Trans. Graph..

[10]  Marie-Pierre Jolly,et al.  Interactive Graph Cuts for Optimal Boundary and Region Segmentation of Objects in N-D Images , 2001, ICCV.

[11]  Marko Heikkilä,et al.  A Texture-based Method for Detecting Moving Objects , 2004, BMVC.

[12]  Michael Beetz,et al.  The Contracting Curve Density Algorithm: Fitting Parametric Curve Models to Images Using Local Self-Adapting Separation Criteria , 2004, International Journal of Computer Vision.

[13]  James C. Gee,et al.  Two--level MRF Models for Image Restoration and Segmentation , 2004, BMVC.

[14]  Pascal Fua,et al.  Texture Boundary Detection for Real-Time Tracking , 2004, ECCV.

[15]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[16]  Marie-Pierre Jolly,et al.  Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[17]  Vladimir Kolmogorov,et al.  "GrabCut": interactive foreground extraction using iterated graph cuts , 2004, ACM Trans. Graph..

[18]  Rama Chellappa,et al.  Contour-based 3D Face Modeling from a Monocular Video , 2004, BMVC.