Adaptive most joint selection and covariance descriptions for a robust skeleton-based human action recognition

In this paper, we propose two effective manners of utilizing skeleton data for human action recognition (HAR). The proposed method on one hand takes advantage of the skeleton data thanks to their robustness to human appearance change as well as the real-time performance. On the other hand, it avoids...

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Veröffentlicht in:	Multimedia tools and applications 2021-07, Vol.80 (18), p.27757-27783
Hauptverfasser:	Nguyen, Van-Toi, Nguyen, Tien-Nam, Le, Thi-Lan, Pham, Dinh-Tan, Vu, Hai
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Communication Networks Computer Science Covariance Data Structures and Information Theory Datasets Feature extraction Human activity recognition Human motion Joints (anatomy) Multimedia Information Systems Neural networks Occlusion Robustness Special Purpose and Application-Based Systems
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