Hand Detection with Dominant Pose Recognition Using EOH and SVM

Chi Min Oh; Seok Jin Lee; Chil Woo Lee

doi:10.4028/www.scientific.net/AMM.571-572.735

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 571-572Hand Detection with Dominant Pose Recognition...

Hand Detection with Dominant Pose Recognition Using EOH and SVM

Abstract:

In this paper we propose a method of vision-based hand detection. Since the pose space of articulated is infinite and it is not feasible to train a classifier for the recognition of all hand poses to detect hand areas. Therefore we assume that it is rather better to detect only one dominant hand pose. To do so after hand skin color segmentation, each interest region of hand area in the given image is validated that the shape of hand region is similar to the dominant pose. The proposed system has the process of two steps; hand candidate detection and dominant pose recognition using EOH feature and SVM classifier. The experimental result shows that the proposed method works very effectively with very low false negative rate 0.6%.

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Periodical:

Applied Mechanics and Materials (Volumes 571-572)

Pages:

735-740

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.571-572.735

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Online since:

June 2014

Authors:

Chi Min Oh*, Seok Jin Lee, Chil Woo Lee

Keywords:

Computer Vision, Hand Detection, Pose Recognition

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