A novel pedestrian re-identification algorithm framework based on deep learning

Huawei Wang; Yijing Guo

doi:10.1117/12.2653790

8 December 2022 A novel pedestrian re-identification algorithm framework based on deep learning

Huawei Wang, Yijing Guo

Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 124740N (2022) https://doi.org/10.1117/12.2653790
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China

Abstract

To further promote the improvement of pedestrian re-identification performance, this paper studies the reid framework based on "reid-strong-baseline", and uses different optimization schemes to improve the network performance. Firstly, the study tests three kinds of loss: Softmax, triplet hard, and Softmax + triplet hard, to verify the Rank-1 performance obtained and which can achieve the best performance. Secondly, based on the prototype network obtained by applying Softmax + triplet hard loss, we utilize several optimization methods including data enhancement, learning rate optimization, sampling method, and Label smoothing. Then we study the effectiveness of these optimizations on the performance of the Baseline model and the degree of improvement. Finally, this paper studies the efficiency of different Backbone and network depths on the performance of pedestrian re-identification.

Citation Download Citation

Huawei Wang and Yijing Guo "A novel pedestrian re-identification algorithm framework based on deep learning", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 124740N (8 December 2022); https://doi.org/10.1117/12.2653790

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KEYWORDS

Data modeling

Process modeling

Image processing

Information technology

Neural networks

Statistical modeling

Machine vision

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