Qian, X.; Yuemaier, A.; Yang, W.; Chen, X.; Liang, L.; Li, S.; Dai, W.; Song, Z. A Self-Organizing Multi-Layer Agent Computing System for Behavioral Clustering Recognition. Sensors2023, 23, 5435.
Qian, X.; Yuemaier, A.; Yang, W.; Chen, X.; Liang, L.; Li, S.; Dai, W.; Song, Z. A Self-Organizing Multi-Layer Agent Computing System for Behavioral Clustering Recognition. Sensors 2023, 23, 5435.
Qian, X.; Yuemaier, A.; Yang, W.; Chen, X.; Liang, L.; Li, S.; Dai, W.; Song, Z. A Self-Organizing Multi-Layer Agent Computing System for Behavioral Clustering Recognition. Sensors2023, 23, 5435.
Qian, X.; Yuemaier, A.; Yang, W.; Chen, X.; Liang, L.; Li, S.; Dai, W.; Song, Z. A Self-Organizing Multi-Layer Agent Computing System for Behavioral Clustering Recognition. Sensors 2023, 23, 5435.
Abstract
Video behavior recognition often needs to focus on object motion processes. In this work, a self-organizing computational system oriented to behavioral clustering recognition is proposed, which achieves the extraction of motion change patterns by binary encoding and completes motion pattern summarization using a similarity comparison algorithm. And in the face of unknown behavioral video data, a self-organizing structure with layer-by-layer accuracy progression is used to achieve motion law summarization by using a multi-layer agent design approach. Finally, the real-time feasibility is verified in the prototype system using real scenes to provide a new feasible solution for unsupervised behavior recognition and space-time scenes.
Engineering, Electrical and Electronic Engineering
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