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Behavior Automatic Analysis for Wolf Pack Hunting: Making Fast Behavior Analysis of Massive Data Possible by Dengqing Tang; Cheng Huang; Xiaojia Xiang; Han Zhou; Shaohao Zhu; Tianjiang Hu is a Agricultural and Biological Sciences article available to read on EtoBox.

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## Abstract Automatic wolf pack hunting behavior analysis contributes to the identification of behavioral mechanism and the development of bio-swarm intelligence engineering. However, wolf pack hunting commonly involves a complicated background and high-speed motion, where the frequent interactions with each other lead to frequent visual occlusion of the individual wolves. These difficulties make the automatic analysis of group hunting behavior significantly more challenging. Hence, we develop an automatic wolf pack hunting behavior detection scheme appropriate for videos, comprising a four-level individual feature map (frame, video, space, and semantic) and a group feature map. We propose a temporal–spatial feature fusion-based motion state recognition algorithm appropriate for scale-varied and occlusion-frequent individuals to obtain a robust semantic-level feature. Based on this individual feature map, we propose a video-based wolf pack hunting automatic behavior detection method. The developed scheme is validated on our Wolf2022 dataset, while the proposed motion state recognition and group behavior detection algorithms are further tested through ablation experiments. The resul

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Author

Dengqing Tang; Cheng Huang; Xiaojia Xiang; Han Zhou; Shaohao Zhu; Tianjiang Hu

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Agricultural and Biological Sciences (Life Sciences)