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The gesture recognition using motion capture data and depth sensors has recently drawn more attention in vision recognition.
Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G., and Williams, R. J. (1986) · 1986
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Hinton, G. and Salakhutdinov, R. (2006) · 2006
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Extreme learning machine: Theory and applications
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Motion templates for automatic classification and retrieval of motion capture data
Müller, M. and Roder, T. (2006) · 2006
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Greedy layer-wise training of deep networks
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Scaling learning algorithms towards AI
Bengio, Y. and LeCun, Y. (2007) · 2007
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Documentation mocap database HDM05
Müller, M., Röder, T., Clausen, M., Eberhardt, B., Krüger, B., and Weber, A. (2007) · 2007
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Classification using discriminative restricted Boltzmann machines
Larochelle, H. and Bengio, Y. (2008) · 2008
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Flexible dictionaries for action classification
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Neural Networks and Learning Machines
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Distance matrices as invariant features for classifying MoCap data
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A real-time system for motion retrieval and interpretation
Barnachon, M., Bouakaz, S., Boufama, B., and Guillou, E. (2013) · 2013
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Classification of rgb-d and motion capture sequences using extreme learning machine
Chen, X. and Koskela, M. (2013) · 2013
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Conditional random field-based gesture recognition with depth information
Chung, H. and Yang, H.-D. (2013) · 2013
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Berkeley mhad: A comprehensive multimodal human action database
Ofli, F., Chaudhry, R., Kurillo, G., Vidal, R., and Bajcsy, R. (2013) · 2013
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Human action recognition based on semi-supervised discriminant analysis with global constraint
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Mining actionlet ensemble for action recognition with depth cameras
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Zhao, X., Li, X., Pang, C., and Wang, S. (2013) · 2013
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