Visual Event Detection Using Multi-Dimensional Concept Dynamics
Date
2006
Authors
Ebadollahi, Shahram
Xie, Lexing
Chang, Shih-Fu
Smith, John R
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
A novel framework is introduced for visual event detection. Visual events are viewed as stochastic temporal processes in the semantic concept space. In this concept-centered approach to visual event modeling, the dynamic pattern of an event is modeled through the collective evolution patterns of the individual semantic concepts in the course of the visual event. Video clips containing different events are classified by employing information about how well their dynamics in the direction of each semantic concept matches those of a given event. Results indicate that such a data-driven statistical approach is in fact effective in detecting different visual events such as exiting car, riot, and airplane flying.
Description
Keywords
Keywords: Dynamic pattern; Event detection; Temporal processes; Computer simulation; Feature extraction; Image retrieval; Multimedia systems; Semantics; Random processes
Citation
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Source
Proceedings IEEE International Conference on Multimedia and Expo (ICME 2006)
Type
Conference paper
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Restricted until
2037-12-31