基于边缘智能终端的跨模态行人重识别方法及应用

Application of Cross-modality Person Re-identificaton based on Edge Intelligent Terminal

跨模态行人重识别技术旨在可见光、红外等不同模态图像中识别出同一个人,其在人机协同、万物互联、跨界融合、万物智能的智能系统与装备中具有重要应用。提出一种数据增强的跨模态行人重识别方法,在波长域进行数据增强的同时保留可见图像的结构信息,以弥合不同模态之间的差距。在此基础上,基于瑞芯微的RK3588芯片设计实现了一套边缘智能终端,并部署了跨模态行人重识别算法。在边缘计算部署的硬件设计、软件开发中,通过模块化的设计、层级配置的方案,实现了系统弹性可扩展,降低了数据集中处理的计算压力。实验结果表明,新方法在两个基准数据集SYSU-MM01和RegDB上取得了较好的性能,并能够在实际场景中进行应用部署。

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.