Abstract
Recently action recognition has been used for a variety of applications such as surveillance, smart homes, and in-home elder monitoring. Such applications usually focus on recognizing human actions without taking into account the different scenarios where the action occurs. In this paper, we propose a two-stream architecture that considers not only the movements to identify the action, but also the context scene where the action is performed. Experiments show that the scene context may improve the recognition of certain actions. Our proposed architecture is tested against baselines and the standard two-stream network.
Original language | English |
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Title of host publication | Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 23rd Iberoamerican Congress, CIARP 2018, Proceedings |
Editors | Ruben Vera-Rodriguez, Julian Fierrez, Aythami Morales |
Publisher | Springer-Verlag |
Pages | 954-961 |
Number of pages | 8 |
ISBN (Print) | 9783030134686 |
DOIs | |
Publication status | Published - 2019 |
Event | 23rd Iberoamerican Congress on Pattern Recognition, CIARP 2018 - Madrid, Spain Duration: 19 Nov 2018 → 22 Nov 2018 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11401 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 23rd Iberoamerican Congress on Pattern Recognition, CIARP 2018 |
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Country/Territory | Spain |
City | Madrid |
Period | 19/11/18 → 22/11/18 |
Bibliographical note
Funding Information:Acknowledgement. The authors would like to thank CAPES/FAPERGS and Motorola Mobility for partially funding this research. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research.
Publisher Copyright:
© Springer Nature Switzerland AG 2019.
Keywords
- Action recognition
- Convolutional Neural Networks
- Neural networks