VideoAL: a novel end-to-end MPEG-7 video automatic labeling system

Author

Lin, Ching-Yung ; Tseng, Belle L. ; Naphade, Milind ; Natsev, Aposfol ; Smith, John R.

Author_Institution

IBM Thomas J. Watson Res. Center, Hawthorne, NY, USA

Volume

3

fYear

2003

fDate

14-17 Sept. 2003

Abstract

In this paper, we describe a novel end-to-end video automatic labeling system, which accepts MPEG-I sequence inputs and generates MPEG-7 XML metadata files based on the prior established anchor models. Seven modules were developed for the system: shot segmentation, region segmentation, annotation, feature extraction, model learning, classification, and XML rendering. The performance of this system has been tested in the NIST TREC-2002 video concept detection benchmark. The proposed system performs best in the mean average precision out of 18 worldwide participants.

Keywords

XML; classification; feature extraction; image segmentation; learning (artificial intelligence); meta data; multimedia systems; video signal processing; MPEG-1 sequence inputs; MPEG-7; XML metadata files; XML rendering; annotation; classification; end-to-end system; feature extraction; model learning; region segmentation; shot segmentation; video automatic labeling system; video concept detection benchmark; Benchmark testing; Detectors; Feature extraction; Gunshot detection systems; Histograms; Labeling; MPEG 7 Standard; NIST; System testing; XML;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on

ISSN

1522-4880

Print_ISBN

0-7803-7750-8

Type

conf

DOI

10.1109/ICIP.2003.1247179

Filename

1247179