Multi-faceted contextual model for person identification in news video

Author

Zhao, Ming ; Neo, Shi-Yong ; Goh, Hai-Kiat ; Chua, Tat-Seng

Author_Institution

Sch. of Comput., Singapore Nat. Univ.

fYear

0

fDate

0-0 0

Abstract

Person identification is very important in the domain of multimedia news as it is often the focus of events in news stories and interest of searchers. However, this detection is impeded by the imprecise audio/visual analysis tools. In this paper, we describe a multimodal and multi-faceted approach to person-x detection in news video. We make use of multimodal features extracted from text, visual and audio inherent in news video. We also incorporate multiple external sources of news from Web and parallel news archives to extract location and temporal profile of the persons. We call this second source of information the multi-faceted context. The multimodal, multi-faceted information is then fused using a rank boosting approach. Experiments on TRECVID 2003 and 2004 search queries demonstrate that our approach is effective

Keywords

feature extraction; object detection; video signal processing; TRECVID; audio-visual analysis; multifaceted contextual model; multimedia new; multimodal feature; news video; person identification; person temporal profile; rank boosting; Automatic speech recognition; Context modeling; Data mining; Face detection; Feature extraction; Home computing; Impedance; Multimedia systems; Optical character recognition software; Target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Multi-Media Modelling Conference Proceedings, 2006 12th International

Conference_Location

Beijing

Print_ISBN

1-4244-0028-7

Type

conf

DOI

10.1109/MMMC.2006.1651320

Filename

1651320