지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
The visual sensing of human hands plays an important part in many man-machine interaction/interface systems. Most existing visionbased hand detection techniques depend on the color cues of human skin. The RGB color image from a vision sensor is often transformed to another color space as a preprocessing of hand detection because the color space transformation is assumed to increase the detection accuracy. However, the actual effect of color space transformation has not been well investigated in literature. This paper discusses a comparative evaluation of the pixel classification performance of hand skin detection in four widely used color spaces; RGB, YIQ, HSV, and normalized rgb. The experimental results indicate that using the normalized red-green color values is the most reliable under different backgrounds, lighting conditions, individuals, and hand postures. The nonlinear classification of pixel colors by the use of a multilayer neural network is also proposed to improve the detection accuracy.
목차
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참고문헌 (15)
참고문헌 신청
A. Wilson / 2003 / Gwindows: Robust stereo vision for gesture-based control of windows / Proc. of Int. Conf. on Multimodal Interfaces : 211 ~ 218
E. Lin / 2002 / Hand tracking using spatial gesture modeling andvirtual feedback for a virtual DJ system / Proc. ofIEEE Int. Conf. on Multimodal Interfaces 197 (202) : 197 ~ 202
F. A. Bertsch / 2009 / Real-time dynamic visual gesture recognition in human-robot interaction / Proc. of IEEE-RAS Int. Conf. on Humanoid Robots : 447 ~ 453
H. I. Christensen / 2001 / Computational vision for interaction with peopleand robots / Proc. Int. Conf. Mechatronics andMachine Vision in Practice
M. B. Holte / 2010 / Viewinvariant gesture recognition using 3D optical flow and harmonic motion context / Comput. Vision Image Understanding 114 (12) : 1353 ~ 1361
E. Lin / 2002 / Hand tracking using spatial gesture modeling andvirtual feedback for a virtual DJ system / Proc. ofIEEE Int. Conf. on Multimodal Interfaces 197 (202) : 197 ~ 202
F. A. Bertsch / 2009 / Real-time dynamic visual gesture recognition in human-robot interaction / Proc. of IEEE-RAS Int. Conf. on Humanoid Robots : 447 ~ 453
H. I. Christensen / 2001 / Computational vision for interaction with peopleand robots / Proc. Int. Conf. Mechatronics andMachine Vision in Practice
M. B. Holte / 2010 / Viewinvariant gesture recognition using 3D optical flow and harmonic motion context / Comput. Vision Image Understanding 114 (12) : 1353 ~ 1361
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