Exploring Concept Selection Strategies for Interactive Video Search

Ranked shot lists from 39 automated LSCOM-Lite concept classifiers are investigated with respect to 24 TRECVID 2006 topics. Selecting the best fitting concept or pair of concepts produces the shot set with greatest utility, rather than drawing fewer shots from a larger set of concepts. Mean average precision measures show concept-based shot sets have great utility for topics when perfectly traversed by a user. Using empirical data, however, shows that realistic ability to separate relevant shots from irrelevant ones and recall all the relevant ones is topic-dependent and far from perfect. Concept-based strategies including user-driven selection strategies not using idealized oracle prioritization are also discussed, with implications for query-by-concept in interactive video retrieval as concept spaces grow from tens to thousands.

[1]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Ching-chih Chen,et al.  Automated semantic annotation and retrieval based on sharable ontology and case-based learning techniques , 2003, 2003 Joint Conference on Digital Libraries, 2003. Proceedings..

[3]  Marcel Worring,et al.  Learned Lexicon-Driven Interactive Video Retrieval , 2006, CIVR.

[4]  Rong Yan,et al.  Probabilistic models for combining diverse knowledge sources in multimedia retrieval , 2006 .

[5]  Alexander G. Hauptmann,et al.  Successful approaches in the TREC video retrieval evaluations , 2004, MULTIMEDIA '04.

[6]  Rong Yan,et al.  Merging storyboard strategies and automatic retrieval for improving interactive video search , 2007, CIVR '07.

[7]  Michael G. Christel.  Establishing the utility of non-text search for news video retrieval with real world users , 2007, ACM Multimedia.

[8]  Michael G. Christel,et al.  Mining Novice User Activity with TRECVID Interactive Retrieval Tasks , 2006, CIVR.

[9]  Milind R. Naphade,et al.  Assessing the Filtering and Browsing Utility of Automatic Semantic Concepts for Multimedia Retrieval , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[10]  Eero Sormunen,et al.  End-User Searching Challenges Indexing Practices in the Digital Newspaper Photo Archive , 2004, Information Retrieval.

[11]  Michael G. Christel,et al.  Finding the right shots: assessing usability and performance of a digital video library interface , 2004, MULTIMEDIA '04.

[12]  Stéphane Marchand-Maillet,et al.  Managing video collections at large , 2004, CVDB '04.

[13]  John R. Smith,et al.  Large-scale concept ontology for multimedia , 2006, IEEE MultiMedia.

[14]  Marcel Worring,et al.  A Learned Lexicon-Driven Paradigm for Interactive Video Retrieval , 2007, IEEE Transactions on Multimedia.