Tracking dynamic near-regular texture under occlusion and rapid movements

Wen Chieh Lin, Yanxi Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Title of host publicationComputer Vision - ECCV 2006, 9th European Conference on Computer Vision, Proceedings
PublisherSpringer Verlag
Pages44-55
Number of pages12
ISBN (Print)3540338349, 9783540338345
StatePublished - Jan 1 2006
Event9th European Conference on Computer Vision, ECCV 2006 - Graz, Austria
Duration: May 7 2006May 13 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3952 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th European Conference on Computer Vision, ECCV 2006
CountryAustria
CityGraz
Period5/7/065/13/06

Fingerprint

Occlusion
Texture
Textures
Lattice Structure
Lighting
Topological Invariants
Geometry
Ambiguous
Random Field
Illumination
Correspondence
Camera
Cameras
Movement
Model
Invariant
Motion
Observation

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Lin, W. C., & Liu, Y. (2006). Tracking dynamic near-regular texture under occlusion and rapid movements. In Computer Vision - ECCV 2006, 9th European Conference on Computer Vision, Proceedings (pp. 44-55). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3952 LNCS). Springer Verlag.
Lin, Wen Chieh ; Liu, Yanxi. / Tracking dynamic near-regular texture under occlusion and rapid movements. Computer Vision - ECCV 2006, 9th European Conference on Computer Vision, Proceedings. Springer Verlag, 2006. pp. 44-55 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Lin, WC & Liu, Y 2006, Tracking dynamic near-regular texture under occlusion and rapid movements. in Computer Vision - ECCV 2006, 9th European Conference on Computer Vision, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3952 LNCS, Springer Verlag, pp. 44-55, 9th European Conference on Computer Vision, ECCV 2006, Graz, Austria, 5/7/06.

Tracking dynamic near-regular texture under occlusion and rapid movements. / Lin, Wen Chieh; Liu, Yanxi.

Computer Vision - ECCV 2006, 9th European Conference on Computer Vision, Proceedings. Springer Verlag, 2006. p. 44-55 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3952 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Lin WC, Liu Y. Tracking dynamic near-regular texture under occlusion and rapid movements. In Computer Vision - ECCV 2006, 9th European Conference on Computer Vision, Proceedings. Springer Verlag. 2006. p. 44-55. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).