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부피 특징 벡터와 3차원 Haar-like 필터를 이용한 조명과 포즈에 강인한 손 검출

Title
부피 특징 벡터와 3차원 Haar-like 필터를 이용한 조명과 포즈에 강인한 손 검출
Authors
안현진
Date Issued
2011
Publisher
포항공과대학교
Abstract
This paper proposes an illumination and pose robust hand detection method using volumetric features and 3D Haar-like filters, which are obtained from AdaBoost learning. Existing hand detection methods using skin color or 2D appearance have the drawback that they are not robust to illumination changes and pose variations. We take volumetric features to get robustness about illumination changes and propose 3D Haar-like filters to get robustness about pose variations. We consider two types of hand detectors that use different 3D Haar-like filters, where one is intended to detect as many hands as possible and the other is intended to verify the detected hands and combine them by a logical AND operation to improve the hand detection performance. We performed several experiments using 2,500 hand images to validate the proposed hand detection method. The experimental results show that (1) the classification performance of volumetric features outperforms those of other features like color and pattern by more than 20%, (2) the classification performance of the combined hand detector outperforms that of the single hand detector by more than 5%, and (3) the detection performance of the proposed hand detector with 3D Haar-like filters is about 90%.
URI
http://postech.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000000923174
http://oasis.postech.ac.kr/handle/2014.oak/1144
Article Type
Thesis
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