HAND GESTURE RECOGNITION BY LOG PATH SIGNATURE FRAMEWORK AND HAND POSE ESTIMATION
Journal Title: World Science - Year 2018, Vol 1, Issue 6
Abstract
Hand gesture recognition and pose estimation is gaining more attentions because it is a natural and intuitive mode of human computer interaction. Hand gesture recognition still faces great challenges for the real-world applications due to the gesture variance and individual difference. The problem of hand pose estimation from passive stereo inputs has received less attention in the literature compared to active depth sensors. This paper seeks to address this gap by presenting a datadriven method to estimate a hand gesture recognition and pose estimation, by introducing a stochastic approach to propose potential depth solutions to the observed stereo capture and evaluate these proposals using convolutional neural networks (CNNs).
Authors and Affiliations
A. G’. G’aybullayev, O’. M. Rayimqulov
Keywords
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- EP ID EP327838
- DOI 10.31435/rsglobal_ws/12062018/5806
- Views 102
- Downloads 0
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