Object trajectory clustering via tensor analysis

Huiyu Zhou*, Dacheng Tao, Yuan Yuan, Xuelong Li

*Corresponding author for this work

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

Abstract

In this paper we present a new video object trajectory clustering algorithm1, which allows us to model and analyse the patterns of object behaviors based on the extracted features using tensor analysis. The proposed algorithm consists of three steps as follows: extraction of trajectory features by tensor analysis, non-parametric probabilistic mean shift clustering and clustering correction. The performance of the proposed algorithm is evaluated on standard data-sets and compared with classical techniques.

Original languageEnglish
Title of host publication2009 16th IEEE International Conference on Image Processing (ICIP)
PublisherIEEE
Pages1945-1948
Number of pages4
ISBN (Print)9781424456543
DOIs
Publication statusPublished - 1 Jan 2009
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, United Kingdom
Duration: 7 Nov 200910 Nov 2009

Conference

Conference2009 IEEE International Conference on Image Processing, ICIP 2009
CountryUnited Kingdom
CityCairo
Period7/11/0910/11/09

Keywords

  • Clustering
  • Mean shift
  • Object trajectory
  • Tensor analysis

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    Zhou, H., Tao, D., Yuan, Y., & Li, X. (2009). Object trajectory clustering via tensor analysis. In 2009 16th IEEE International Conference on Image Processing (ICIP) (pp. 1945-1948). IEEE. https://doi.org/10.1109/ICIP.2009.5414536