Automatic calibration and speed estimation on multi-directional vehicle flow

• Main Author: Ibarrientos, Chester Paul
• Format: text
• Language: English
• Published: Animo Repository 2018
• Subjects: Automobiles > Speed; Calibration
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/5532
• Institution: De La Salle University

This research aims to create a speed detection system that can automatically calibrate to scenes with vehicles moving in multiple directions. Specific areas such as intersections and curved roads satisfy the condition of multi-directional movement. There is a substantial amount of research on calibration and speed estimation, however, existing methods only focus on vehicles moving in straight lines. In this paper, the current approaches on calibration and speed estimation are investigated and a novel approach for calibrating on multi-directional vehicle movement is proposed. Two vanishing points are detected from the scene. The first vanishing point is detected by a Cascaded Hough Transform. Previous works detect the second vanishing point using edges from vehicles. However, this does not work if the vehicles are not aligned with the perspective. Hence, to detect the second vanishing point, a multiple regression t is used to derive the horizontal position of the second vanishing point from the location of the first vanishing point. To further handle multi-directional movement, motion lines from vehicle movement are used to detect the alignment of vehicles and the dimensions of the bounding boxes are adjusted accordingly based on the detected alignment. Results show that the system is able to calibrate to different perspectives and estimate the speed of the vehicles. The estimated distances from the calibration process have an average absolute error of about 1.87 meters and an average relative error of 18.56%. This translates to a speed estimation error of plus or minus 6.74 kilometers per hour.