Person Re-Identification with Model-Contrastive Federated Learning in Edge-Cloud Environment
Baixuan Tang1,2,#, Xiaolong Xu1,2,#, Fei Dai3, Song Wang4,*
Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 35-55, 2023, DOI:10.32604/iasc.2023.036715
- 26 January 2024
Abstract Person re-identification (ReID) aims to recognize the same person in multiple images from different camera views. Training person ReID models are time-consuming and resource-intensive; thus, cloud computing is an appropriate model training solution. However, the required massive personal data for training contain private information with a significant risk of data leakage in cloud environments, leading to significant communication overheads. This paper proposes a federated person ReID method with model-contrastive learning (MOON) in an edge-cloud environment, named FRM. Specifically, based on federated partial averaging, MOON warmup is added to correct the local training of individual edge… More >