Romanian Journal of Information Technology and Automatic Control / Vol. 35, No. 2, 2025

Prototyping a graph-based approach for efficient vehicle tracking in a cluster controlled CCTV surveillance systems

Apurva NARAYAN, Charumathi PARIVALLAL, Olirva MAHESWARAN, Sarath CHANDRAN KALATHILPARAMBIL RAMACHANDRAN

Abstract:

In this work, an advanced multimodal video summarization system is developed for a cluster-controlled traffic surveillance environment. Addressing the growing challenges of vehicle density and traffic complexity, the system employs state-of-the-art deep learning techniques for real-time vehicle detection, tracking, and route analysis. Utilizing algorithms like YOLO for object detection, the system ensures an accurate and efficient monitoring across multiple surveillance nodes. The optical character recognition (OCR) enables a detailed number plate recognition, while the multimodal data fusion enhances the robustness of vehicle tracking in dynamic conditions. Supported by data pipelines and frameworks, the system processes extensive CCTV footage to generate concise video summaries, optimizing the surveillance operations. The architecture offers scalable and adaptive solutions, aiming to improve the traffic management and emergency response by providing actionable insights through seamless integration of visual, audio, and textual data. This innovation has the potential to set new benchmarks in the intelligent traffic surveillance systems, with significant implications for public safety and urban mobility.

Keywords:
Multimodal Video Summarization, Traffic Surveillance System, CCTV Footage Analysis, Realtime Monitoring, Urban Mobility.

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CITE THIS PAPER AS:
Apurva NARAYAN, Charumathi PARIVALLAL, Olirva MAHESWARAN, Sarath CHANDRAN KALATHILPARAMBIL RAMACHANDRAN, "Prototyping a graph-based approach for efficient vehicle tracking in a cluster controlled CCTV surveillance systems", Romanian Journal of Information Technology and Automatic Control, ISSN 1220-1758, vol. 35(2), pp. 99-109, 2025. https://doi.org/10.33436/v35i2y202508