High level feature: Head and body co-trakcing by Kalman filter

Chun Hua Chen, Chung Yuan Lin, Sz Yan Li, Tsung Han Tsai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Tracking multiple targets in complex situation is challenging. The difficulties are tackled multiple targets with occlusions, especially when multiple involved targets are grouped and moving together in appearance. In this paper, we present a multiple targets tracking system for the management of occlusion problem. The proposed algorithm introduces a geometric shape co-tracking strategy. It decomposes targets into geometric shapes located on body and head parts based on reasonable target geometry consideration. Features selected from the decomposed geometric shapes then can be used to track targets through intersections such as occlusion. Projection histogram and ellipsoid shape model are adopted to manage decomposed geometric shapes corresponding to each target. Tracking is done through Kalman filtering process with high efficient and low complexity issue. Experimental results show that the occlusion of grouped targets can be tracked successfully on recent challenging benchmark sequences.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages725-728
Number of pages4
DOIs
StatePublished - 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: 26 Sep 201029 Sep 2010

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/TerritoryHong Kong
CityHong Kong
Period26/09/1029/09/10

Keywords

  • Correspondence
  • Feature extraction
  • Kalman filter
  • Morphological
  • Shape
  • Tracking

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