PVSS: A Progressive Vehicle Search System for Video Surveillance Networks
Xinchen Liu, Wu Liu, Huadong Ma, Shuangqun Li

TL;DR
This paper introduces PVSS, a comprehensive vehicle search system for surveillance networks that integrates detection, indexing, and progressive search to improve accuracy despite environmental challenges.
Contribution
The paper presents a novel, integrated vehicle search system with a progressive search process, addressing detection, representation, and matching issues in surveillance scenarios.
Findings
PVSS achieves high accuracy on real surveillance datasets.
The system effectively handles intra-camera variations and low-resolution challenges.
Extensive experiments validate the system's robustness and efficiency.
Abstract
This paper is focused on the task of searching for a specific vehicle that appeared in the surveillance networks. Existing methods usually assume the vehicle images are well cropped from the surveillance videos, then use visual attributes, like colors and types, or license plate numbers to match the target vehicle in the image set. However, a complete vehicle search system should consider the problems of vehicle detection, representation, indexing, storage, matching, and so on. Besides, attribute-based search cannot accurately find the same vehicle due to intra-instance changes in different cameras and the extremely uncertain environment. Moreover, the license plates may be misrecognized in surveillance scenes due to the low resolution and noise. In this paper, a Progressive Vehicle Search System, named as PVSS, is designed to solve the above problems. PVSS is constituted of three…
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Taxonomy
TopicsVideo Surveillance and Tracking Methods · Advanced Image and Video Retrieval Techniques · Advanced Neural Network Applications
