Vehicle Re-identification for Visual Surveillance
Intelligent video surveillance systems are becoming an increasingly important major area of artificial intelligence as the use of motor vehicles in today’s transportation networks grows. In recent times re-identifying vehicles over a surveillance camera network have been proven to be the most effective method of efficiently controlling traffic, upholding the law, gathering information, and programming the traffic. Vehicle Re-ID seeks to recognize a target vehicle in several, non-overlapping camera perspectives. Compared to the common person re-ID issue, it has gotten far less attention in the computer vision community. The absence of pertinent research data and the unique 3D structure of a vehicle are two potential causes of this delayed progression.
This research presents PAK Vehicle Re-ID Dataset (PV-ReID) with arbitrary viewpoints including unique vehicle identities based on Asian regions like Pakistan and India. In addition, a generalized pipeline for vehicle re-identification systems is presented.