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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44058

Title: Human Smoking Event Detection using Visual Interaction Clues
Authors: Pin Wu
Jun-Wei Hsieh
Jiun-Cheng Cheng
Shyi-Chyi Cheng
Shau-Yin Tseng
Contributors: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
Keywords: Face
Humans
Image color analysis
Histograms
Pixel
Visualization
Pattern recognition
Date: 2010-08
Issue Date: 2017-11-13T08:02:49Z
Publisher: IEEE International Conference on Pattern Recognition
Abstract: Abstract:This paper presents a novel scheme to automatically and directly detect smoking events in video. In this scheme, a color-based ratio histogram analysis is introduced to extract the visual clues from appearance interactions between lighted cigarette and its human holder. The techniques of color re-projection and Gaussian Mixture Models (GMMs) enable the tasks of cigarette segmentation and tracking over the background pixels. Then, a key problem for event analysis is the non-regular form of smoking events. Thus, we propose a self-determined mechanism to analyze this suspicious event using HHM framework. Due to the uncertainties of cigarette size and color, there is no automatic system which can well analyze human smoking events directly from videos. The proposed scheme is compatible to detect the smoking events of uncertain actions with various cigarette sizes, colors, and shapes, and has capacity to extend visual analysis to human events of similar interaction relationship. Experimental results show the effectiveness and real-time performances of our scheme in smoking event analysis.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44058
Appears in Collections:[資訊工程學系] 演講及研討會

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