论文标题
人重新识别
Person Re-Identification
论文作者
论文摘要
人重新识别（RE-ID）是基于计算机视觉的监视应用中的一个重要问题，在基于计算机视觉的监视应用中，人们旨在识别从具有不同方向和视野不同的不同相机拍摄的不同监视照片中的人。由于对智能视频监视的需求不断增长，Re-ID对计算机视觉社区产生了浓厚的兴趣。在这项工作中，我们尝试了一些现有的重新ID方法，这些方法在某些开放基准中获得了最新性能的状态。我们在定性和定量上分析其在提供的数据集上的性能，然后提出改善结果的方法。这项工作是在IIT德里提交的COL780最终项目的报告。
Person Re-Identification (Re-ID) is an important problem in computer vision-based surveillance applications, in which one aims to identify a person across different surveillance photographs taken from different cameras having varying orientations and field of views. Due to the increasing demand for intelligent video surveillance, Re-ID has gained significant interest in the computer vision community. In this work, we experiment on some existing Re-ID methods that obtain state of the art performance in some open benchmarks. We qualitatively and quantitaively analyse their performance on a provided dataset, and then propose methods to improve the results. This work was the report submitted for COL780 final project at IIT Delhi.
