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.
翻译：人搜索的目的是在现场图像的画廊中寻找一个具有广泛应用的探测器,例如罪犯搜索、多相机跟踪、失踪人搜索等。 早期人搜索工作侧重于以图像为基础的人搜索,以人图像为搜索查询工具。基于文本的人搜索是另一个主要的人搜索类别,以自由形式自然语言为搜索查询工具。 人搜索具有挑战性,相应的解决方案是多种多样和复杂的。因此,关于这一专题的系统调查至关重要。本文从挑战和解决方案的角度对最近关于基于图像和基于文本的人搜索的作品进行了调查。具体地说,我们对具有高度影响力的人搜索方法进行了简要分析,其中考虑到三大挑战:歧视人的特征、询问人的差距和检测识别特征的不一致。我们总结和比较了评估结果。最后,我们讨论了公开的问题和一些有希望的未来研究方向。
相关内容
微信扫码咨询专知VIP会员