BOOK

Concept-Based Video Retrieval

Abstract

Concept-Based Video Retrieval reviews 300 references on video retrieval, indicating when the text-only solutions of present-day video search engines are unsatisfactory and showing the promising alternatives which are primarily concept-based. Central to the discussion, therefore, is the fundamental notion of a semantic concept: an objective linguistic description of an observable entity. The book aims to motivate and explain how automated detection, selection under uncertainty, and interactive usage might solve the major scientific problems for video retrieval: the semantic gap. In striving to bridge this gap, the authors structured their review by laying down the anatomy of a concept-based video search engine. They present a component-wise decomposition and evaluation of such an interdisciplinary multimedia system, covering influences from information retrieval, computer vision, machine learning, and human-computer interaction. Concept-Based Video Retrieval is aimed primarily at researchers and developers in the broad area of information retrieval. It will also be an invaluable reference for students in computer and information science at the (post)graduate level, as well as industrial practitioners

Keywords:
Computer science Information retrieval Video retrieval Semantic gap Bridge (graph theory) Selection (genetic algorithm) Component (thermodynamics) Cognitive models of information retrieval Multimedia Human–computer information retrieval Multimedia information retrieval World Wide Web Search engine Image retrieval Artificial intelligence Image (mathematics)

Metrics

322
Cited By
7.49
FWCI (Field Weighted Citation Impact)
306
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Analysis and Summarization
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

Related Documents

JOURNAL ARTICLE

Concept-Based Video Retrieval

Cees G. M. SnoekMarcel Worring

Journal:   Foundations and Trends® in Information Retrieval Year: 2009 Vol: 2 (4)Pages: 215-322
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