Preprint Communication Version 1 Preserved in Portico This version is not peer-reviewed

A Self-Organizing Multi-Layer Agent Computing System for Behavioral Clustering Recognition

Xingyu Qian
ORCID logo ,
Aximu Yuemaier
,
Wen-Chi Yang
,
Xiaogang Chen
* ORCID logo ,
Longfei Liang
,
Shunfen Li
,
Weibang Dai
,
Zhitang Song
Version 1 : Received: 8 May 2023 / Approved: 10 May 2023 / Online: 10 May 2023 (11:07:29 CEST)

A peer-reviewed article of this Preprint also exists.

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. 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.

Keywords

field programmable gate array (FPGA); hardware implementation; real-time system; action clustering

Subject

Engineering, Electrical and Electronic Engineering

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download PDF

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0
Get PDF Cite Share 0
Bookmark BibSonomy Mendeley Reddit Delicious
×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.