Aug 2026· Applied Sciences· 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
A traffic flow statistics system based on YOLOv8 object detection algorithm and ByteTrack multi-target tracking algorithm that has good practical value and prospects for promotion and application, and provides a technical basis for the subsequent introduction of infrared thermal imaging multimodal fusion to enhance low...
Experimental results demonstrate that the proposed framework achieves high classification performance while maintaining an effective balance between detection accuracy and computational efficiency, indicating that the proposed method may offer a practical approach for ITS applications involving low-resolution surveilla...
Yaser 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
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