DeepHand: Robust Hand Pose Estimation by Completing a Matrix Imputed with Deep Features - Convergence Design Lab, Purdue University
purdue.edu
DeepHand: Robust Hand Pose Estimation by Completing a Matrix Imputed with Deep Features - Convergence Design Lab, Purdue University
We propose DeepHand to estimate the 3D pose of a hand using depth data from commercial 3D sensors. We discriminatively train convolutional neural networks to output a low dimensional activation feature given a depth map. This activation feature vector is representative of the global or local joint angle parameters of a hand pose. We efficiently
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