Special Issue on Deep Learning-Based Action Recognition
1. Introduction
2. Scope of Action Recognition
3. Deep Learning-Based Action Recognition
4. Future Action Recognition
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Fortes Rey, V.; Garewal, K.K.; Lukowicz, P. Translating Videos into Synthetic Training Data for Wearable Sensor-Based Activity Recognition Systems Using Residual Deep Convolutional Networks. Appl. Sci. 2021, 11, 3094. [Google Scholar] [CrossRef]
- Dawar, N.; Kehtarnavaz, N. Continuous detection and recognition of actions of interest among actions of non-interest using a depth camera. In Proceedings of the IEEE International Conference on Image Processing, Beijing, China, 17–20 September 2017. [Google Scholar]
- Hu, K.; Zheng, F.; Weng, L.; Ding, Y.; Jin, J. Action Recognition Algorithm of Spatio–Temporal Differential LSTM Based on Feature Enhancement. Appl. Sci. 2021, 11, 7876. [Google Scholar] [CrossRef]
- Wei, H.; Laszewski, M.; Kehtarnavaz, N. Deep Learning-Based Person Detection and Classification for Far Field Video Surveillance. In Proceedings of the 13th IEEE Dallas Circuits and Systems Conference, Dallas, TX, USA, 2–12 November 2018. [Google Scholar]
- Chu, Y.-C.; Jhang, Y.-J.; Tai, T.-M.; Hwang, W.-J. Recognition of Hand Gesture Sequences by Accelerometers and Gyroscopes. Appl. Sci. 2020, 10, 6507. [Google Scholar] [CrossRef]
- Fangbemi, A.; Liu, B.; Yu, N.; Zhang, Y. Efficient Human Action Recognition Interface for Augmented and Virtual Realty Applications Based on Binary Descriptor. In Proceedings of the 5th International Conference, AVR 2018, Ontranto, Italy, 24–27 June 2018. [Google Scholar]
- Wu, J.; Lee, H.-J. A New Multi-Person Pose Estimation Method Using the Partitioned CenterPose Network. Appl. Sci. 2021, 11, 4241. [Google Scholar] [CrossRef]
- Kim, S.-T.; Lee, H.J. Lightweight Stacked Hourglass Network for Human Pose Estimation. Appl. Sci. 2020, 10, 6497. [Google Scholar] [CrossRef]
- Tasnim, N.; Islam, M.K.; Baek, J.-H. Deep Learning Based Human Activity Recognition Using Spatio-Temporal Image Formation of Skeleton Joints. Appl. Sci. 2021, 11, 2675. [Google Scholar] [CrossRef]
- Chen, L.; Ma, N.; Wang, P.; Li, J.; Wang, P.; Pang, G.; Shi, X. Survey of pedestrian action recognition techniques for autonomous driving. Tsinghua Sci. Technol. 2020, 25, 458–470. [Google Scholar] [CrossRef]
- Nguyen, N.-H.; Phan, T.-D.-T.; Kim, S.-H.; Yang, H.-J.; Lee, G.-S. 3D Skeletal Joints-Based Hand Gesture Spotting and Classification. Appl. Sci. 2021, 11, 4689. [Google Scholar] [CrossRef]
- Kim, J.; Cho, J. Low-Cost Embedded System Using Convolutional Neural Networks-Based Spatiotemporal Feature Map for Real-Time Human Action Recognition. Appl. Sci. 2021, 11, 4940. [Google Scholar] [CrossRef]
- Dong, J.; Gao, Y.; Lee, H.J.; Zhou, H.; Yao, Y.; Fang, Z.; Huang, B. Action Recognition Based on the Fusion of Graph Convolutional Networks with High Order Features. Appl. Sci. 2020, 10, 1482. [Google Scholar] [CrossRef] [Green Version]
- Nguyen, N.-H.; Phan, T.-D.-T.; Lee, G.-S.; Kim, S.-H.; Yang, H.-J. Gesture Recognition Based on 3D Human Pose Estimation and Body Part Segmentation for RGB Data Input. Appl. Sci. 2020, 10, 6188. [Google Scholar] [CrossRef]
- Stergiou, A.; Poppe, R.; Veltkamp, R.C. Learning Class-Specific Features with Class Regularization for Videos. Appl. Sci. 2020, 10, 6241. [Google Scholar] [CrossRef]
- Do, N.-T.; Kim, S.-H.; Yang, H.-J.; Lee, G.-S. Robust Hand Shape Features for Dynamic Hand Gesture Recognition Using Multi-Level Feature LSTM. Appl. Sci. 2020, 10, 6293. [Google Scholar] [CrossRef]
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Lee, H.J. Special Issue on Deep Learning-Based Action Recognition. Appl. Sci. 2022, 12, 7834. https://doi.org/10.3390/app12157834
Lee HJ. Special Issue on Deep Learning-Based Action Recognition. Applied Sciences. 2022; 12(15):7834. https://doi.org/10.3390/app12157834
Chicago/Turabian StyleLee, Hyo Jong. 2022. "Special Issue on Deep Learning-Based Action Recognition" Applied Sciences 12, no. 15: 7834. https://doi.org/10.3390/app12157834
APA StyleLee, H. J. (2022). Special Issue on Deep Learning-Based Action Recognition. Applied Sciences, 12(15), 7834. https://doi.org/10.3390/app12157834