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An Efficient Face Region Detection for Content-based Video Summarization  

Kim Jong-Sung (한국항공대학교 정보통신공학과 대학원 멀티미디어검색연구실)
Lee Sun-Ta (한국항공대학교 정보통신공학과 대학원 멀티미디어검색연구실)
Baek Joong-Hwan (한국항공대학교 항공전자 및 정보통신공학부)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.30, no.7C, 2005 , pp. 675-686 More about this Journal
Abstract
In this paper, we propose an efficient face region detection technique for the content-based video summarization. To segment video, shot changes are detected from a video sequence and key frames are selected from the shots. We select one frame that has the least difference between neighboring frames in each shot. The proposed face detection algorithm detects face region from selected key frames. And then, we provide user with summarized frames included face region that has an important meaning in dramas or movies. Using Bayes classification rule and statistical characteristic of the skin pixels, face regions are detected in the frames. After skin detection, we adopt the projection method to segment an image(frame) into face region and non-face region. The segmented regions are candidates of the face object and they include many false detected regions. So, we design a classifier to minimize false lesion using CART. From SGLD matrices, we extract the textual feature values such as Inertial, Inverse Difference, and Correlation. As a result of our experiment, proposed face detection algorithm shows a good performance for the key frames with a complex and variant background. And our system provides key frames included the face region for user as video summarized information.
Keywords
video summarization; face detection; video indexing; CART; SGLO; spatial gray level dependence matrix;
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