RGB-D-based human motion recognition with deep learning: A survey

@article{Wang2018RGBDbasedHM,
  title={RGB-D-based human motion recognition with deep learning: A survey},
  author={Pichao Wang and Wanqing Li and Philip Ogunbona and Jun Wan and Sergio Escalera},
  journal={Computer Vision and Image Understanding},
  year={2018},
  volume={171},
  pages={118-139}
}
Human motion recognition is one of the most important branches of human-centered research activities. In recent years, motion recognition based on RGB-D data has attracted much attention. Along with the development in artificial intelligence, deep learning techniques have gained remarkable success in computer vision. In particular, convolutional neural networks (CNN) have achieved great success for image-based tasks, and recurrent neural networks (RNN) are renowned for sequence-based problems… CONTINUE READING
Related Discussions
This paper has been referenced on Twitter 31 times. VIEW TWEETS

Citations

Publications citing this paper.
Showing 1-10 of 12 extracted citations

Beyond Two-stream: Skeleton-based Three-stream Networks for Action Recognition in Videos

2018 24th International Conference on Pattern Recognition (ICPR) • 2018
View 5 Excerpts
Highly Influenced

References

Publications referenced by this paper.
Showing 1-10 of 184 references

Deep Learning on Lie Groups for Skeleton-Based Action Recognition

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) • 2017
View 6 Excerpts
Highly Influenced

Ensemble Deep Learning for Skeleton-Based Action Recognition Using Temporal Sliding LSTM Networks

2017 IEEE International Conference on Computer Vision (ICCV) • 2017
View 5 Excerpts
Highly Influenced

Generalized Rank Pooling for Activity Recognition

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) • 2017
View 4 Excerpts
Highly Influenced

RPAN: An End-to-End Recurrent Pose-Attention Network for Action Recognition in Videos

2017 IEEE International Conference on Computer Vision (ICCV) • 2017
View 7 Excerpts
Highly Influenced

Tube Convolutional Neural Network (T-CNN) for Action Detection in Videos

2017 IEEE International Conference on Computer Vision (ICCV) • 2017
View 7 Excerpts
Highly Influenced

Unsupervised Learning of Long-Term Motion Dynamics for Videos

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) • 2017
View 8 Excerpts
Highly Influenced

A unified framework for multi-modal isolated gesture recognition

J. Duan, S. Zhou, J. Wan, X. Guo, S. Z. Li
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) • 2016
View 4 Excerpts
Highly Influenced

Dynamic Image Networks for Action Recognition

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) • 2016
View 12 Excerpts
Highly Influenced

NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) • 2016
View 5 Excerpts
Highly Influenced