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http://dx.doi.org/10.5391/JKIIS.2013.23.6.551

Part-based Hand Detection Using HOG  

Baek, Jeonghyun (School of Electrical and Electronics Engineering, Yonsei University)
Kim, Jisu (School of Electrical and Electronics Engineering, Yonsei University)
Yoon, Changyong (Department of Electrical Engineering, Suwon Science College)
Kim, Dong-Yeon (Electrical, Electronic and Control Engineering, Hankyong National University)
Kim, Euntai (School of Electrical and Electronics Engineering, Yonsei University)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.23, no.6, 2013 , pp. 551-557 More about this Journal
Abstract
In intelligent robot research, hand gesture recognition has been an important issue. And techniques that recognize simple gestures are commercialized in smart phone, smart TV for swiping screen or volume control. For gesture recognition, robust hand detection is important and necessary but it is challenging because hand shape is complex and hard to be detected in cluttered background, variant illumination. In this paper, we propose efficient hand detection algorithm for detecting pointing hand for recognition of place where user pointed. To minimize false detections, ROIs are generated within the compact search region using skin color detection result. The ROIs are verified by HOG-SVM and pointing direction is computed by both detection results of head-shoulder and hand. In experiment, it is shown that proposed method shows good performance for hand detection.
Keywords
Gesture Recognition; Hand Detection; HOG; SVM; HCI; Skin Color Detection;
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