Tracking system using texture cue based on wavelet transform

This paper presents an approach for tracking objects whose principal discriminate characteristic is its texture. The presented system extracts texture features based on the wavelet transform and uses a fuzzy grammar classifier. The feature vector consists of 6 characteristics extracted from the wavelet detail images. The overall system was integrated on the platform developed by sony – AIBO robot. This application ensures a real time tracking approach and can be parameterized in order to be flexible in face of different types of texture.

[1]  S. Livens,et al.  Image analysis for material characterisation , 1998 .

[2]  Hai Tao,et al.  Object Tracking using Color Correlogram , 2005, 2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance.

[3]  Lindsay Kleeman,et al.  Fusion of multimodal visual cues for model-based object tracking , 2003 .

[4]  Bedrich J. Hosticka,et al.  Unsupervised texture segmentation of images using tuned matched Gabor filters , 1995, IEEE Trans. Image Process..

[5]  B. Ripley,et al.  Pattern Recognition , 1968, Nature.

[6]  B. Torrésani,et al.  Wavelets: Mathematics and Applications , 1994 .

[7]  Cedric Nishan Canagarajah,et al.  A robust automatic clustering scheme for image segmentation using wavelets , 1996, IEEE Trans. Image Process..

[8]  Dariu Gavrila,et al.  A Bayesian Framework for Multi-cue 3D Object Tracking , 2004, ECCV.

[9]  Andrew W. Appel,et al.  Modern Compiler Implementation in ML , 1997 .

[10]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[11]  Xin Li,et al.  Contour-based object tracking with occlusion handling in video acquired using mobile cameras , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Taylor L. Booth,et al.  Grammatical Inference: Introduction and Survey-Part II , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  C. Burrus,et al.  Introduction to Wavelets and Wavelet Transforms: A Primer , 1997 .

[14]  Ashutosh Malaviya.  On-line handwriting recognition with a fuzzy feature description language , 1996 .

[15]  Jf Baldwin,et al.  An Introduction to Fuzzy Logic Applications in Intelligent Systems , 1992 .

[16]  Liliane Peters,et al.  An automatic rule base generation method for fuzzy pattern recognition with multiphased clustering , 1998, 1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111).

[17]  Liliane Peters,et al.  A Fuzzy Statistical Rule Generation Method for Handwriting Recognition , 1998 .

[18]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

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

[20]  Barry T. Thomas,et al.  Supervised segmentation and tracking of nonrigid objects using a "mixture of histograms" model , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[21]  Sankar K. Pal,et al.  Fuzzy Mathematical Approach to Pattern Recognition , 1986 .

[22]  Éric Marchand,et al.  Real time planar structure tracking for visual servoing: a contour and texture approach , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Lotfi A. Zadeh,et al.  Note on fuzzy languages , 1969, Inf. Sci..

[24]  Sankar K. Pal,et al.  Fuzzy models for pattern recognition , 1992 .

[25]  Paul S Williams.  The automatic hierarchical decomposition of images into sub-images for use in image recognition and classification , 1999 .

[26]  Gary R. Bradski,et al.  Real time face and object tracking as a component of a perceptual user interface , 1998, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201).

[27]  Gert Van De Wouwer,et al.  Wavelets For Multiscale Texture Analysis , 1998 .