Research on person Re-ID based on joint attention mechanism

Hongjun Chen; Lei Ma; Liheng Zhao

doi:10.1117/12.2637068

15 June 2022 Research on person Re-ID based on joint attention mechanism

Hongjun Chen, Lei Ma, Liheng Zhao

Proceedings Volume 12285, International Conference on Advanced Algorithms and Neural Networks (AANN 2022); 122850D (2022) https://doi.org/10.1117/12.2637068
Event: International Conference on Advanced Algorithms and Neural Networks (AANN 2022), 2022, Zhuhai, China

Abstract

Re-ID is a technology to judge whether there is a specific pedestrian in the image or video. Attention mechanism is applied into Re-ID to optimize the feature representation and improve the discrimination characteristics of features. This paper studies the mechanism of Dual Joint Attention (DJA), which optimizes feature representation by paying attention to local important features and capturing global context in spatial domain and channel domain respectively. And use DJA to build a model. In the classification of the model, A-softmax is used as the loss function which clusters the features in the angle space by imposing the multiplicative angle interval constraint, so as to directly integrate the metric learning into the classification. Experiments show that mAP and Rank-1 are significantly improved.

Citation Download Citation

Hongjun Chen, Lei Ma, and Liheng Zhao "Research on person Re-ID based on joint attention mechanism", Proc. SPIE 12285, International Conference on Advanced Algorithms and Neural Networks (AANN 2022), 122850D (15 June 2022); https://doi.org/10.1117/12.2637068

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KEYWORDS

Convolution

Video surveillance

Computer vision technology

Feature extraction

Integration

Machine vision

Performance modeling

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