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Hierarchical aggregation perceptual pipeline for tactical intention recognition

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Abstract

Tactical intention recognition involves the analysis of target information to interpret and accurately determine hostile intentions, which is crucial for auxiliary decision-making. The recognition challenges are posed by hierarchical and long-term dependencies in tactical intention. To this end, we propose a pipeline that enhances intention recognition performance by perceiving and aggregating the hierarchy information within the tactical context, termed Hierarchical Aggregation Perceptual Pipeline (HAGP). Specifically, the HAGP comprises two pipelines: maneuver features perceive (MFP), and intention features aggregate (IFA). The MFP captures the maneuver features, which are sub-intentioned with hierarchical information, and the IFA aggregates long-term dependencies in each intention. Then, combining these representations to facilitate precise tactical intention recognition. Extensive experimental results on the tactical dataset demonstrate the superiority of our pipeline compared with the state-of-the-art methods.

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Data Availability

Raw data for the dataset is not publicly available to preserve individuals’ privacy under the Northwestern Polytechnical University Data Protection Regulation.

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Acknowledgements

This work has been supported by these following projects: (1) Grant No. D5120190078, National Science and technology projects of China. (2) Grant No. D5140190006, Key R & D projects of Shaanxi Province.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Northwestern Polytechnical University, 1 Dongxiang Road, Xi’an, Shaanxi, 710129, China

    Ying Li, Junsheng Wu, Wei Dong & Aiqing Fang

  2. School of Software, Northwestern Polytechnical University, 1 Dongxiang Road, Xi’an, Shaanxi, 710129, China

    Weigang Li

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  1. Ying Li
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Correspondence to Weigang Li.

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Li, Y., Wu, J., Li, W. et al. Hierarchical aggregation perceptual pipeline for tactical intention recognition. Multimed Tools Appl 83, 58245–58265 (2024). https://doi.org/10.1007/s11042-023-17806-4

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