View Adaptive Neural Networks for High Performance Skeleton-Based Human Action Recognition
Xi'an Jiaotong University · Microsoft Research Asia (China) · +2 more institutions
Abstract
Skeleton-based human action recognition has recently attracted increasing attention thanks to the accessibility and the popularity of 3D skeleton data. One of the key challenges in action recognition lies in the large variations of action representations when they are captured from different viewpoints. In order to alleviate the effects of view variations, this paper introduces a novel view adaptation scheme, which automatically determines the virtual observation viewpoints over the course of an action in a learning based data driven manner. Instead of re-positioning the skeletons using a fixed human-defined prior criterion, we design two view adaptive neural networks, i.e., VA-RNN and VA-CNN, which are…
Citation impact
- FWCI
- 28.37
- Percentile
- 100%
- References
- 82
Authors
6Topics & keywords
- Viewpoints
- Computer science
- Artificial intelligence
- Convolutional neural network
- Machine learning
- Artificial neural network
- Deep learning
- Recurrent neural network