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arXiv · 1510.09171

Accurate Vision-based Vehicle Localization using Satellite Imagery

Hang Chu·Hongyuan Mei·Mohit Bansal·Matthew R. Walter
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Abstract

We propose a method for accurately localizing ground vehicles with the aid of satellite imagery. Our approach takes a ground image as input, and outputs the location from which it was taken on a georeferenced satellite image. We perform visual localization by estimating the co-occurrence probabilities between the ground and satellite images based on a ground-satellite feature dictionary. The method is able to estimate likelihoods over arbitrary locations without the need for a dense ground image database. We present a ranking-loss based algorithm that learns location-discriminative feature projection matrices that result in further improvements in accuracy. We evaluate our method on the Malaga and KITTI public datasets and demonstrate significant improvements over a baseline that performs exhaustive search.

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Hang Chu, Hongyuan Mei, Mohit Bansal, Matthew R. Walter. 2015-10-30. Accurate Vision-based Vehicle Localization using Satellite Imagery. https://arxiv.org/abs/1510.09171

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