Aug 2026· Applied Sciences· Vol 16, pp. 8541· 0 citations· 18 references
TL;DR
A perception-tracking-reasoning framework based on traffic rules, which is used for vehicle recognition and driving-state analysis in surveillance videos is proposed, which integrates enhanced vehicle perception, cross-frame identity association, trajectory-state modeling, and interpretable rule reasoning into a unified processing flow.
Abstract
Traditional traffic target detection heavily relies on manual processing. However, the latest advancements in deep learning have significantly enhanced the capabilities of target detection and multi-target tracking. To address these challenges, this paper proposes a perception-tracking-reasoning framework based on traffic rules, which is used for vehicle recognition and driving-state analysis in surveillance videos. This framework integrates enhanced vehicle perception, cross-frame identity association, trajectory-state modeling, and interpretable rule reasoning into a unified processing flow. Finally, experiments show that the main advantage of the proposed model lies in its ability to detect small-sized vehicle targets and improve trajectory stability in complex traffic scenarios.
A streamlined vehicle detection framework that combines background subtraction for motion-oriented foreground extraction with a Haar cascade classifier for object identification in traffic video sequences is introduced, suggesting that classical computer vision techniques remain viable alternatives for real-time traffi...
Ni Gusti Ayu Dasriani, Anthony Anggrawan, Khasnur Hidjah et al.· International Journal of Inf...· 0 citations
Autonomous vehicles depend on fast and reliable perception systems to detect surrounding vehicles, pedestrians, cyclists, traffic signs, and other road objects in real time. This paper presents a comprehensive survey and analysis of one-stage object detectors for autonomous driving rather than an implementation of a ne...
Jonel Roman, Ryan Sirjue, Peter Nguyen et al.· 0 citations
This article addresses the issues of high deployment costs, low accuracy in small object detection, and easy ID switching in multi-target tracking of existing traffic flow statistics methods. Based on the visual sensing mechanism of visible light imaging, this article designs and implements a traffic flow statistics sy...
Vehicle detection and classification play a crucial role in the effective implementation of Intelligent Transportation System (ITS) applications. Due to their superior feature representation capabilities, convolutional neural network (CNN)-based deep learning models have become strong candidates for vehicle detection...
Y. Dalveren, Bamoye Maiga, Ali Kara et al.· Scientific Reports· 0 citations
The installation of a real-time visual tracking system with an active pan-tilt camera for indoor human motion detection is presented, which shows that the inclusion of YOLOv10 significantly improves detection precision and temporal consistency.
Ayman Javid Hussain, Lalitha Saroja Ch, Ruqiya Fatima· International Journal of AI...· 0 citations
An adaptive occlusion-aware multi vehicle tracking model that improves robustness under varying illumination, congestion, and occlusion conditions while maintaining efficient performance is presented.
Ekta Ukey, Satishkumar L. Varma· WSEAS Transactions on Signal...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
