Robust multi-level video representation using mean shift analysis

Author

Gao, Hai ; Yu, Xiaodong ; Wang, Lei ; Xue, Ping ; Tian, Qi

Author_Institution

Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore

Volume

1

fYear

2004

fDate

30-30 June 2004

Firstpage

627

Abstract

A robust method for multi-level video representation based on the mean shift analysis (MSA) of low-level visual features is proposed in this paper. By tuning the bandwidth of MSA, video representation from the coarse level to the fine level can be achieved. This representation form provides a flexible scheme for content-based video analysis such as summarization, classification, and retrieval. Compared with the conventional k-means or fuzzy c-means algorithms, our method can adjust the resolution of representation in a more straightforward way, and is more robust since it does not need to initialize the cluster centers

Keywords

content-based retrieval; feature extraction; image classification; image representation; image retrieval; video signal processing; classification; content-based video analysis; low-level visual features; mean shift analysis; retrieval; robust multi-level video representation; summarization; Bandwidth; Clustering algorithms; Color; Content based retrieval; Indexing; Information retrieval; Iterative algorithms; Motion analysis; Robustness; Video sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia and Expo, 2004. ICME '04. 2004 IEEE International Conference on

Conference_Location

Taipei

Print_ISBN

0-7803-8603-5

Type

conf

DOI

10.1109/ICME.2004.1394270

Filename

1394270