Abstract

Pedestrian re-identification (Re-ID) is an emerging cutting-edge technology in the research area of intelligentvideo analysis in recent years, belonging to the category of image processing and analysis in complex video environments. This technology plays a crucial role in numerous monitoring and security applications and has been a hot topic in computer vision research. Pedestrian re-identification is considered an important sub-problem in image retrieval, which involves using computer vision algorithms to match pedestrian images or videos across devices to identify the same pedestrian from image databases of different monitoring devices. Research in this area can be traced back to the 1990s when researchers proposed various methods to address the challenge of pedestrian re-identification. This article summarizes the relevant research on personnel re-identification based on deep learning technology and its applications in different scenarios. Besides, it also identifies existing problems with this technology and its prospects.

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