Real-time tracking of human hands from a sign-language image sequence

Imagawa, Kazuyuki; Lu, Shan; Igi, Satoshi

doi:10.1007/3-540-63930-6_184

Cited by 2 publications

(1 citation statement)

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“…Hand occlusion is the main challenge in hands tracking, because not only the overlapping often occurs, but also the hand size and the hand orientation are both changing during occlusion. Many systems like (Schreer, 2005), (Kirubarajan and BarShalom, 2001), (Coogan, 2006) and (Imagawa, 1998) will warn the user to separate hands when occlusion is detected and the systems will restart tracking after then.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Hand Locating by Monocular Vision

Ding¹,

Wang²,

Chaillou³

et al. 2010

Proceedings of the International Conference on Computer Vision Theory and Applications

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The research on real-time hand locating by monocular vision has a considerable challenge that to track hands correctly under occlusion situation. This paper proposes a robust hand locating method which generates a possibility support map by integrating information from color model, position model and motion model. For better accuracy, hands are modeled as ellipses. The PSM depends on both previous model information and the relationship between models. Hand pattern search is then processed on the generated map by two steps which firstly locates the center position of hand and secondly determines the size and orientation. Our experimental results show that the proposed method is efficient under situation that one hand is occluded by the other one. Our current prototype system processes image at 10~14 frames per second.

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Section: Related Workmentioning

confidence: 99%