@inproceedings{9eb0754ae4374945837a558952a5786e,
title = "A comprehensive test framework to determine the spatial performance of camera-based vehicle detection algorithms",
abstract = "This paper proposes a performance test framework for vision based vehicle detection systems implemented on road-going vehicles. An extensive literature review outlines the evolution of test frameworks used by a number of recently published vehicle detection systems. The proposed test framework determines the effectiveness of a detection algorithm as a function of distance between the host and target vehicles. The framework assists the characterisation of an algorithm's performance over the full range of distances in which a vehicle can be detected in an image. The test framework is designed for use in blind spot detection, forward collision warning and rear end collision warning applications.",
keywords = "automotive vision, blind spot detection, fish-eye lens, forward collision warning, Image processing, rear-end collision warning",
author = "Damien Dooley and Brian McGinley and Liam Kilmartin and Edward Jones and Martin Glavin and Ciar{\'a}n Hughes",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014 ; Conference date: 10-12-2014 Through 12-12-2014",
year = "2014",
doi = "10.1109/ICARCV.2014.7064335",
language = "English",
series = "2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "377--382",
booktitle = "2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014",
}