关键词: 行人再识别, 深度学习, 多源信息行人再识别

Abstract:

With the continuous development of computer vision technology, pedestrian re-identification technology has played a huge role in the fields of security, detection and intelligent surveillance, and has become a current research hotspot. The traditional pedestrian re-recognition technology focuses on the research of the visual information of the RGB image collected by the camera, and has achieved good results under laboratory conditions, but under adverse conditions such as poor lighting, occlusion of objects, and blurred image quality, the recognition rate of the algorithm has experienced a cliff-like decline. Nowadays, visual information does not only focus on RGB images, but also introduces information such as infrared images, depth images, and sketch portraits to improve the recognition rate of the algorithm. At the same time, the application of text information and spatiotemporal information also improves the performance of pedestrian re-recognition algorithms. However, due to the natural differences between the various modes, how to connect multiple kinds of information has become the main problem of multi-source information pedestrian re-identification research. This article combs the research papers on pedestrian re-identification with multiple sources of information published in recent years, expounds the current situation, technical difficulties and future development trends of pedestrian re-identification.

Key words: pedestrian re-identification, deep learning, multi-source information pedestrian re-identification