Person Re-Identification
This is an incremental improvement for computer vision-based surveillance applications.
The paper tackles the problem of person re-identification in surveillance by analyzing existing state-of-the-art methods on a dataset and proposing improvements, but does not report specific numerical results.
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.