Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates
Nanyang Technological University · The University of Sydney · +1 more institution
Abstract
Skeleton-based human action recognition has attracted a lot of research attention during the past few years. Recent works attempted to utilize recurrent neural networks to model the temporal dependencies between the 3D positional configurations of human body joints for better analysis of human activities in the skeletal data. The proposed work extends this idea to spatial domain as well as temporal domain to better analyze the hidden sources of action-related information within the human skeleton sequences in both of these domains simultaneously. Based on the pictorial structure of Kinect's skeletal data, an effective tree-structure based traversal framework is also proposed. In order to deal with the noise in…
Citation impact
- FWCI
- 16.73
- Percentile
- 100%
- References
- 122
Authors
5Topics & keywords
- Computer science
- Artificial intelligence
- Tree traversal
- Context (archaeology)
- Benchmark (surveying)
- Domain (mathematical analysis)
- Noise (video)
- Representation (politics)