NDLI: An interactive video content-based retrieval system

Content Provider	IEEE Xplore Digital Library
Author	Camara-Chavez, G. Precioso, F. Cord, M. Phillip-Foliguet, S. de A. Araujo, A.
Copyright Year	2008
Description	Author affiliation: CNRS, Equipe Traitement des Images et du Signal-ENSEA, Pontoise (Camara-Chavez, G.; Precioso, F.; Cord, M.; Phillip-Foliguet, S.)
Abstract	The actual generation of video search engines offers low-level abstractions of the data while users seek for high-level semantics. The main challenge in video retrieval remains bridging the semantic gap. Thus, the effectiveness of video retrieval is based on the result of the interaction between query selection and a goal-oriented human user. The system exploits the human capability for rapidly scanning imagery augmenting it with an active learning loop, which tries to always present the most relevant material based on the current information. We describe in this paper, a machine learning system for interactive video retrieval. The core of this system is a kernel-based SVM classifier. The video retrieval uses the core as an active learning classifier. We perform an experiment against the 2005 NIST TRECVID benchmark in the high-level task.
Starting Page	133
Ending Page	136
File Size	648349
Page Count	4
File Format	PDF
ISBN	9788022728560
DOI	10.1109/IWSSIP.2008.4604385
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	Slovakia
Access Restriction	Subscribed
Rights Holder	15th International Conference on Systems, Signals and Image Processing
Subject Keyword	Support vector machines Training Image color analysis shot boundary detection retrieval Machine learning video indexing Feature extraction Multimedia communication Indexing
Content Type	Text
Resource Type	Article

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