Tracking Dynamic Near-Regular Texture Under Occlusion and Rapid Movements

  • Wen-Chieh Lin
  • Yanxi Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3952)


We present a dynamic near-regular texture (NRT) tracking algorithm nested in a lattice-based Markov-Random-Field (MRF) model of a 3D spatiotemporal space. One basic observation used in our work is that the lattice structure of a dynamic NRT remains invariant despite its drastic geometry or appearance variations. On the other hand, dynamic NRT imposes special computational challenges to the state of the art tracking algorithms: including highly ambiguous correspondences, occlusions, and drastic illumination and appearance variations. Our tracking algorithm takes advantage of the topological invariant property of the dynamic NRT by combining a global lattice structure that characterizes the topological constraint among multiple textons and an image observation model that handles local geometry and appearance variations. Without any assumptions on the types of motion, camera model or lighting conditions, our tracking algorithm can effectively capture the varying underlying lattice structure of a dynamic NRT in different real world examples, including moving cloth, underwater patterns and marching crowd.


Tracking Algorithm Markov Random Field Tracking Process Active Appearance Model Subdivision Surface 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wen-Chieh Lin
    • 1
  • Yanxi Liu
    • 2
  1. 1.College of Computer ScienceNational Chiao-Tung UniversityTaiwan
  2. 2.School of Computer ScienceCarnegie Mellon UniversityUSA

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