SDIGRU: Spatial and Deep Features Integration Using Multilayer Gated Recurrent Unit for Human Activity Recognition
Author:
Affiliation:
1. School of Information and Communication Engineering, Guilin University of Electronic Technology, Guilin, China
2. School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin, China
Funder
China Guangxi Science and Technology Plan Project
Chile CONICYT FONDECYT Regular
Chile CONICYT FONDEF
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Human-Computer Interaction,Social Sciences (miscellaneous),Modeling and Simulation
Link
http://xplorestaging.ieee.org/ielx7/6570650/10414252/10064701.pdf?arnumber=10064701
Reference51 articles.
1. Semantic Event Fusion of Different Visual Modality Concepts for Activity Recognition
2. A survey on vision-based human action recognition
3. Recognizing human actions: a local SVM approach
4. Recognising action as clouds of space-time interest points
5. Action MACH a spatio-temporal Maximum Average Correlation Height filter for action recognition
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