<span>Vehicle and vehicle license detection obtained incredible achievements during recent years that are also popularly used in real traffic scenarios, such as intelligent monitoring systems, auto parking services. Computer vision attracted much attention detection, benefit from image processing machine learning technologies. However, the existing methods still have some issues with plat...

and Normalized Cut Clustering Jui-Chen Wu, Jun-Wei Hsieh * , Yung-Sheng Chen, and Cheng-Min Tu Department of Electrical Engineering Yuan Ze University, Taiwan *[email protected] Abstract This paper proposes a novel approach for vehicle orientation detection using “vehicle color” and edge information based on clustering framework. To extract the “vehicle color”, this paper proposes a novel...

Vehicle trajectories contain rich information on microscopic phenomena such as car following and lane changing. Despite many efforts to retrieve reliable trajectories from video images, previous approaches do not give high enough quality of trajectories that can be used in microscopic analysis. We introduce a new vehicle tracking approach based on a model-based 3-D vehicle detection and descrip...

Automatic traffic scene analysis which has been used for real-time on-road vehicle detection system is essential to many areas of ITS (Intelligent Transport Systems). In order to improve the detection time and accuracy of detection performance, various image processing techniques have been used for real-time vehicle detection. Moreover, Neural Networks have been increasingly and successfully ap...

Land navigation requires a vehicle to steer clear of trees, rocks, and man-made obstacles in the vehicle's path while vehicles in flight, such as helicopters, must avoid antennas, towers, poles, fences, tree branches, and wires strung across the flight path. Automatic detection of these obstacles and the necessary guidance and control actions triggered by such detection would facilitate autonom...

Video-based vehicle detection has received considerable attention over the last ten years and there are many deep learning based detection methods which can be utilized to solve the problem. However, these methods are devised for still images and applying them for video vehicle detection directly always obtain poor performance. In this work, we propose a new one-stage video-based vehicle detect...