A survey of approaches and trends in person re-identification

Person re-identification is a fundamental task in automated video surveillance and has been an area of intense research in the past few years. Given an image/video of a person taken from one camera, re-identification is the process of identifying the person from images/videos taken from a different camera. Re-identification is indispensable in establishing consistent labeling across multiple cameras or even within the same camera to re-establish disconnected or lost tracks. Apart from surveillance it has applications in robotics, multimedia and forensics. Person re-identification is a difficult problem because of the visual ambiguity and spatiotemporal uncertainty in a person's appearance across different cameras. These difficulties are often compounded by low resolution images or poor quality video feeds with large amounts of unrelated information in them that does not aid re-identification. The spatial or temporal conditions to constrain the problem are hard to capture. However, the problem has received significant attention from the computer vision research community due to its wide applicability and utility. In this paper, we explore the problem of person re-identification and discuss the current solutions. Open issues and challenges of the problem are highlighted with a discussion on potential directions for further research.

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