A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions

SK Yadav, K Tiwari, HM Pandey, SA Akbar - Knowledge-Based Systems, 2021 - Elsevier
Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …

Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges

HF Nweke, YW Teh, MA Al-Garadi, UR Alo - Expert Systems with …, 2018 - Elsevier
Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …

Vision-based human activity recognition: a survey

DR Beddiar, B Nini, M Sabokrou, A Hadid - Multimedia Tools and …, 2020 - Springer
Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …

Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding

J Liu, A Shahroudy, M Perez, G Wang… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Research on depth-based human activity analysis achieved outstanding performance and
demonstrated the effectiveness of 3D representation for action recognition. The existing …

A survey of human activity recognition in smart homes based on IoT sensors algorithms: Taxonomies, challenges, and opportunities with deep learning

D Bouchabou, SM Nguyen, C Lohr, B LeDuc… - Sensors, 2021 - mdpi.com
Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of
sensors have encouraged the development of smart environments, such as smart homes …

Ntu rgb+ d: A large scale dataset for 3d human activity analysis

A Shahroudy, J Liu, TT Ng… - Proceedings of the IEEE …, 2016 - openaccess.thecvf.com
Recent approaches in depth-based human activity analysis achieved outstanding
performance and proved the effectiveness of 3D representation for classification of action …

Interpretable 3d human action analysis with temporal convolutional networks

T Soo Kim, A Reiter - … of the IEEE conference on computer …, 2017 - openaccess.thecvf.com
The discriminative power of modern deep learning models for 3D human action recognition
is growing ever so potent. In conjunction with the recent resurgence of 3D human action …

View adaptive neural networks for high performance skeleton-based human action recognition

P Zhang, C Lan, J Xing, W Zeng, J Xue… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
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 …

Global context-aware attention lstm networks for 3d action recognition

J Liu, G Wang, P Hu, LY Duan… - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
Abstract Long Short-Term Memory (LSTM) networks have shown superior performance in
3D human action recognition due to their power in modeling the dynamics and …

View adaptive recurrent neural networks for high performance human action recognition from skeleton data

P Zhang, C Lan, J Xing, W Zeng… - Proceedings of the …, 2017 - openaccess.thecvf.com
Skeleton-based human action recognition has recently attracted increasing attention due to
the popularity of 3D skeleton data. One main challenge lies in the large view variations in …