Fast and Improved Real-Time Vehicle Anti-Tracking System

Safety on roads and the prevention of accidents have become major problems in the world. Intelligent cars are now a standard in the future of transportation. Drivers will benefit from the increased support for driving assistance. This means relying on the development of integrated systems that can p...

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Main Authors: Olivier Oheka, Chunling Tu
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/10/17/5928
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author Olivier Oheka
Chunling Tu
author_facet Olivier Oheka
Chunling Tu
author_sort Olivier Oheka
collection DOAJ
description Safety on roads and the prevention of accidents have become major problems in the world. Intelligent cars are now a standard in the future of transportation. Drivers will benefit from the increased support for driving assistance. This means relying on the development of integrated systems that can provide real-time information to help drivers make decisions. Therefore, computer vision systems and algorithms are needed to detect and track vehicles. This helps traffic management and driving assistance. This paper focuses on developing a reliable vehicle tracking system to detect the vehicle that is following the host vehicle. The proposed system uses a unique approach consisting of a mixture of background removal techniques, Haar features in a modified Adaboost algorithm in a cascade configuration, and SURF descriptors for tracking. From the camera mounted at the rear of the host vehicle, videos are captured. The results presented in this paper demonstrate the potential and efficiency of the system.
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spelling doaj.art-ed3fbd90b4fa433d9cc988d2d9820ae12023-11-20T11:32:06ZengMDPI AGApplied Sciences2076-34172020-08-011017592810.3390/app10175928Fast and Improved Real-Time Vehicle Anti-Tracking SystemOlivier Oheka0Chunling Tu1Department of Computer Systems Engineering, Tshwane University of Technology, Pretoria 0001, South AfricaDepartment of Computer Systems Engineering, Tshwane University of Technology, Pretoria 0001, South AfricaSafety on roads and the prevention of accidents have become major problems in the world. Intelligent cars are now a standard in the future of transportation. Drivers will benefit from the increased support for driving assistance. This means relying on the development of integrated systems that can provide real-time information to help drivers make decisions. Therefore, computer vision systems and algorithms are needed to detect and track vehicles. This helps traffic management and driving assistance. This paper focuses on developing a reliable vehicle tracking system to detect the vehicle that is following the host vehicle. The proposed system uses a unique approach consisting of a mixture of background removal techniques, Haar features in a modified Adaboost algorithm in a cascade configuration, and SURF descriptors for tracking. From the camera mounted at the rear of the host vehicle, videos are captured. The results presented in this paper demonstrate the potential and efficiency of the system.https://www.mdpi.com/2076-3417/10/17/5928vehicle detectionvehicle trackingvehicle recognitioncomputer visiondriving assistance
spellingShingle Olivier Oheka
Chunling Tu
Fast and Improved Real-Time Vehicle Anti-Tracking System
Applied Sciences
vehicle detection
vehicle tracking
vehicle recognition
computer vision
driving assistance
title Fast and Improved Real-Time Vehicle Anti-Tracking System
title_full Fast and Improved Real-Time Vehicle Anti-Tracking System
title_fullStr Fast and Improved Real-Time Vehicle Anti-Tracking System
title_full_unstemmed Fast and Improved Real-Time Vehicle Anti-Tracking System
title_short Fast and Improved Real-Time Vehicle Anti-Tracking System
title_sort fast and improved real time vehicle anti tracking system
topic vehicle detection
vehicle tracking
vehicle recognition
computer vision
driving assistance
url https://www.mdpi.com/2076-3417/10/17/5928
work_keys_str_mv AT olivieroheka fastandimprovedrealtimevehicleantitrackingsystem
AT chunlingtu fastandimprovedrealtimevehicleantitrackingsystem