  Person search has drawn increasing attention due to its real-world
applications and research significance. Person search aims to find a probe
person in a gallery of scene images with a wide range of applications, such as
criminals search, multicamera tracking, missing person search, etc. Early
person search works focused on image-based person search, which uses person
image as the search query. Text-based person search is another major person
search category that uses free-form natural language as the search query.
Person search is challenging, and corresponding solutions are diverse and
complex. Therefore, systematic surveys on this topic are essential. This paper
surveyed the recent works on image-based and text-based person search from the
perspective of challenges and solutions. Specifically, we provide a brief
analysis of highly influential person search methods considering the three
significant challenges: the discriminative person features, the query-person
gap, and the detection-identification inconsistency. We summarise and compare
evaluation results. Finally, we discuss open issues and some promising future
research directions.
