Jump to : Download | Abstract | Contact | BibTex reference | EndNote reference |


Winston Hsu, Shih-Fu Chang. Topic Tracking across Broadcast News Videos with Visual Duplicates and Semantic Concepts. In International Conference on Image Processing (ICIP), Atlanta, GA, USA, 2006.

Download [help]

Download paper: Adobe portable document (pdf)

Copyright notice:This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.


Videos from distributed sources (e.g., broadcasts, podcasts, blogs, etc.) have grown exponentially. Topic threading is very useful for organizing such large-volume information sources. Current solutions primarily rely on text features only but encounter difficulty when text is noisy or unavailable. In this paper, we propose new representations and similarity measures for news videos based on low-level features, visual near-duplicates, and high-level semantic concepts automatically detected from videos. We develop a multimodal fusion framework for estimating relevance of a new story to a known topic. Our extensive experiments using TRECVID 2005 data set (171 hours, 6 channels, 3 languages) confirm that near- duplicates consistently and significantly boost the tracking performance by up to 25%. In addition, we present information-theoretic analysis to assess the complexity of each semantic topic and determine the best subset of concepts for tracking each topic.


Winston Hsu
Shih-Fu Chang

BibTex Reference

   Author = {Hsu, Winston and Chang, Shih-Fu},
   Title = {Topic Tracking across Broadcast News Videos with Visual Duplicates and Semantic Concepts},
   BookTitle = {International Conference on Image Processing (ICIP)},
   Address = {Atlanta, GA, USA},
   Year = {2006}

EndNote Reference [help]

Get EndNote Reference (.ref)


For problems or questions regarding this web site contact The Web Master.

This document was translated automatically from BibTEX by bib2html (Copyright 2003 © Eric Marchand, INRIA, Vista Project).