Training a Feedback Loop for Hand Pose Estimation

Abstract

We propose an entirely data-driven approach to estimating the 3D pose of a hand given a depth image. We show that we can correct the mistakes made by a Convolutional Neural Network trained to predict an estimate of the 3D pose by using a feedback loop. The components of this feedback loop are also Deep Networks, optimized using training data. They remove… (More)
DOI: 10.1109/ICCV.2015.379
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