Semantic video content analysis

Massimiliano Albanese, Pavan Turaga, Rama Chellappa, Andrea Pugliese, V. S. Subrahmanian

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

In recent years, there has been significant interest in the area of automatically recognizing activities occurring in a camera's field of view and detecting abnormalities. The practical applications of such a system could include airport tarmac monitoring, or monitoring of activities in secure installations, to name a few. The difficulty of the problem is compounded by several factors: detection of primitive actions in spite of changes in illumination, occlusions and noise; complexmultiagent interaction;mapping of higher-level activities to lower-level primitive actions; variations in which the same semantic activity can be performed. In this chapter, we develop a theory of semantic activity analysis that addresses each of these issues in an integrated manner. Specifically, we discuss ontological representations of knowledge of a domain, integration of domain knowledge and statistical models for achieving semantic mappings, definition of logical languages to describe activities, and design of frameworks which integrate all the above aspects in a coherent way, thus laying the foundations of effective Semantic Video Content Analysis systems.

Original languageEnglish (US)
Title of host publicationVideo Search and Mining
EditorsDan Schonfeld, Caifeng Shan, Dacheng Tao, Liang Wang
Pages147-176
Number of pages30
DOIs
StatePublished - 2010

Publication series

NameStudies in Computational Intelligence
Volume287
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence

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