基于边缘智能终端的跨模态行人重识别方法及应用

Cross-modallity person re-identification technology (cm-ReID) aims to identify the same person in visible and infrared images. It has crucial applications in intelligent systems and equipment for human-machine cooperation, Internet of everything, cross-border integration, and intelligence of everything. In this paper, we propose a cross-modality person re-identification method based on data enhancement, which preserves the structural information of the visible image while performing data enhancement in the wavelength domain to bridge the gap between different modalities. On this basis, a set of edge intelligent terminals are designed and implemented based on the RK3588 chip and a cross-modality person re-identification algorithm is deployed. In the hardware design and software development of edge computing deployment, the system is flexible and scalable through modular design and hierarchical configuration, reducing the computing pressure of centralized data processing. The experimental results show that the proposed method has performed well on two benchmark data sets, SYSU-MM01 and RegDB, and can be deployed in practical scenarios.