Vehicle Detection Using Imaging Technologies and its Applications under Varying Environments: A Review

Robust and efficient vehicle detection from images is an important task in Intelligent Transportation Systems. With the development of computer vision techniques and consequent accessibility of video image data, new applications have been enabled to on-road vehicle detection algorithms. This paper provides a review of the literature in vehicle detection under varying environments. Due to the variability of on-road driving environments, vehicle detection may face different problems and challenges. Therefore, many approaches have been proposed to detect vehicles, such as feature-based method and model-based methods. In addition, special illumination, weather and driving scenarios are discussed in terms of methodology and quantitative evaluation. In the future, works should be focused on robust vehicle detection approaches for various on-road conditions.