Accessible Unlicensed Requires Authentication Published by De Gruyter 2020

15 Vehicle Ego-Localization with a Monocular Camera Using Epipolar Geometry Constraints

Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide and Hiroshi Murase

Abstract

Nowadays, the development of driving support systems and autonomous driving systems have become active. Vehicle ego-localization using in-vehicle sensors is one of the most important technologies for these systems. Accordingly, various attempts to localize own vehicle from in-vehicle sensors have been made. In general, the estimation accuracy of the traveling direction is lower than in the lateral direction. Therefore, we present a highly accurate method for ego-localization of the traveling direction based on epipolar geometry using an in-vehicle monocular camera. The presented method makes correspondences between in-vehicle camera images and database images with location information, and calculates the location using locations annotated to the corresponding database images. However, there are many gaps due to the difference in speed and trajectory of vehicles even if the images are obtained along the same road. To overcome this problem, the distance between the input image and the database image is calculated by the distance metric based on the epipolar geometry and the local feature method. An experiment was conducted using actual images with correct locations, and the effectiveness of the presented method was confirmed from its results.

© 2020 Walter de Gruyter GmbH, Berlin/Munich/Boston