TY - GEN
T1 - Using scene context to improve action recognition
AU - Monteiro, Juarez
AU - Granada, Roger
AU - Meneguzzi, Felipe
AU - Barros, Rodrigo Coelho
N1 - 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.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Action recognition
KW - Convolutional Neural Networks
KW - Neural networks
UR - http://www.scopus.com/inward/record.url?scp=85063044065&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-13469-3_110
DO - 10.1007/978-3-030-13469-3_110
M3 - Published conference contribution
AN - SCOPUS:85063044065
SN - 9783030134686
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 954
EP - 961
BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 23rd Iberoamerican Congress, CIARP 2018, Proceedings
A2 - Vera-Rodriguez, Ruben
A2 - Fierrez, Julian
A2 - Morales, Aythami
PB - Springer-Verlag
T2 - 23rd Iberoamerican Congress on Pattern Recognition, CIARP 2018
Y2 - 19 November 2018 through 22 November 2018
ER -