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Methods and Comparisons Between Computer Vision and Radar Based Vehicle Location...

by Deniz Aykac, Regina K Ferrell, Nisha Srinivas, Thomas P Karnowski
Publication Type
Conference Paper
Book Title
Electronic Imaging, Intelligent Robotics and Industrial Applications using Computer Vision 2021
Publication Date
Page Numbers
1 to 7
Volume
334
Conference Name
Electronic imaging 2021
Conference Location
Burlingame, California, United States of America
Conference Sponsor
Society for Imaging Science and Technology
Conference Date
-

Measuring vehicle locations relative to a driver's vehicle is a critical component in the analysis of driving data from both postanalysis (such as in naturalistic driving studies) or in autonomous vehicle navigation. In this work we describe a method to estimate vehicle positions from a forward-looking video camera using intrinsic camera calibration, estimates of extrinsic parameters, and a convolutional neural network trained to detect and locate vehicles in video data. We compare the measurements we achieve with this method with ground truth and with radar data available from a naturalistic driving study. We identify regions where video is preferred, where radar is preferred, and explore trade-offs between the two methods in regions where the preference is more ambiguous. We describe applications of these measurements for transportation analysis.