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Recurrent Attention Models for Depth-Based Person Identification
[article]
2016
arXiv
pre-print
We present an attention-based model that reasons on human body shape and motion dynamics to identify individuals in the absence of RGB information, hence in the dark. Our approach leverages unique 4D spatio-temporal signatures to address the identification problem across days. Formulated as a reinforcement learning task, our model is based on a combination of convolutional and recurrent neural networks with the goal of identifying small, discriminative regions indicative of human identity. We
arXiv:1611.07212v1
fatcat:btybowthaba4jnwju2gh3y6yzu