Object trajectory clustering via tensor analysis

Author

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

Author_Institution

Brunel Univ., Uxbridge, UK

fYear

2009

fDate

7-10 Nov. 2009

Firstpage

1945

Lastpage

1948

Abstract

In this paper we present a new video object trajectory clustering algorithm, 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.

Keywords

feature extraction; pattern clustering; probability; video signal processing; clustering correction; nonparametric probabilistic mean shift clustering; object behaviors; tensor analysis; trajectory feature extraction; video object trajectory clustering algorithm; Algorithm design and analysis; Clustering algorithms; Content addressable storage; Data engineering; Feature extraction; Linear discriminant analysis; Matrix decomposition; Optical computing; Pattern analysis; Tensile stress; Object trajectory; clustering; mean shift; tensor analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2009 16th IEEE International Conference on

Conference_Location

Cairo

ISSN

1522-4880

Print_ISBN

978-1-4244-5653-6

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2009.5414536

Filename

5414536