A real-time system for high-level video representation: application to video surveillance

Aishy Amer; Eric Dubois; Amar Mitiche

doi:10.1117/12.476352

7 May 2003 A real-time system for high-level video representation: application to video surveillance

Aishy Amer, Eric Dubois, Amar Mitiche

Author Affiliations +

Proceedings Volume 5022, Image and Video Communications and Processing 2003; (2003) https://doi.org/10.1117/12.476352
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

The steadily increasing need for video content accessibility necessitates the development of stable systems to represent video sequences based on their high-level (semantic) content. The core of such systems is the automatic extraction of video content. In this paper, a computational layered framework to effectively extract multiple high-level features of a video shot is presented. The objective with this framework is to extract rich high-level video descriptions of real world scenes. In our framework, high-level descriptions are related to moving objects which are represented by their spatio-temporal low-level features. High-level features are represented by generic high-level object features such as events. To achieve higher applicability, descriptions are extracted independently of the video context. Our framework is based on four interacting video processing layers: enhancement to estimate and reduce noise, stabilization to compensate for global changes, analysis to extract meaningful objects, and interpretation to extract context-independent semantic features. The effectiveness and real-time response of the our framework are demonstrated by extensive experimentation on indoor and outdoor video shots in the presence of multi-object occlusion, noise, and artifacts.

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Aishy Amer, Eric Dubois, and Amar Mitiche "A real-time system for high-level video representation: application to video surveillance", Proc. SPIE 5022, Image and Video Communications and Processing 2003, (7 May 2003); https://doi.org/10.1117/12.476352

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