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2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017) (2017)
Washington, DC, DC, USA
May 30, 2017 to June 3, 2017
ISBN: 978-1-5090-4023-0
pp: 476-483
ABSTRACT
The interest in action and gesture recognition has grown considerably in the last years. In this paper, we present a survey on current deep learning methodologies for action and gesture recognition in image sequences. We introduce a taxonomy that summarizes important aspects of deep learning for approaching both tasks. We review the details of the proposed architectures, fusion strategies, main datasets, and competitions. We summarize and discuss the main works proposed so far with particular interest on how they treat the temporal dimension of data, discussing their main features and identify opportunities and challenges for future research.
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CITATION
Maryam Asadi-Aghbolaghi, Albert Clapes, Marco Bellantonio, Hugo Jair Escalante, Victor Ponce-Lopez, Xavier Baro, Isabelle Guyon, Shohreh Kasaei, Sergio Escalera, "A Survey on Deep Learning Based Approaches for Action and Gesture Recognition in Image Sequences", 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), vol. 00, no. , pp. 476-483, 2017, doi:10.1109/FG.2017.150
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