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Implementing and Evaluating a Tracking-By-Detection Algorithm for a Camera Monitoring System

  • In this paper, we designed, implemented, and tested a special surveillance camera system based on a combination of classical image processing algorithms. The system’s sub-objective consists of tracking experimental vehicles driving on a defined trajectories (Rail) in real time. Furthermore, it analyzes the scene to collect additional vehicles & rail-related information. The system then uses the gathered data to reach its main objective which confines oneself in independently predicting vehicles collision. Consequently, we propose a hybrid method of detecting and tracking ATLAS-vehicles efficiently. To detect the vehicle at the beginning of the video, periodically every n-frame, and in the case where the tracked vehicle has been lost, we used Histogram Back-Projection. By contrast, Kernelized correlation filter is used to track the detected vehicles. Combining these two methods provides one of the best trade-offs between accuracy and speed even on a single processing core. The proposed method achieves the best performance compared with three different approaches on a custom dataset.

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Author:Khaled Jbaili, Jan Thomanek
Parent Title (German):26. Interdisziplinäre Wissenschaftliche Konferenz Mittweida
Publisher:Hochschule Mittweida
Place of publication:Mittweida
Document Type:Conference Proceeding
Year of Completion:2021
Publishing Institution:Hochschule Mittweida
Release Date:2021/05/21
Tag:Object Detection and Tracking; Planar Homography
Page Number:10
First Page:193
Last Page:204
Open Access:Frei zugänglich
Licence (German):License LogoEs gilt das UrhG