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Proceedings Paper

Human visual system-based smoking event detection
Author(s): Amjad D. Odetallah; Sos S. Agaian
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Paper Abstract

Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

Paper Details

Date Published: 8 May 2012
PDF: 12 pages
Proc. SPIE 8406, Mobile Multimedia/Image Processing, Security, and Applications 2012, 840607 (8 May 2012); doi: 10.1117/12.918773
Show Author Affiliations
Amjad D. Odetallah, The Univ. of Texas at San Antonio (United States)
Sos S. Agaian, The Univ. of Texas at San Antonio (United States)

Published in SPIE Proceedings Vol. 8406:
Mobile Multimedia/Image Processing, Security, and Applications 2012
Sos S. Agaian; Sabah A. Jassim; Eliza Yingzi Du, Editor(s)

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