We propose an accurate ego-localization method by searching a streetview database composed of single front-view in-vehicle camera images. Previously, we proposed an image distance metric reflecting the positional relation of two cameras based on epipolar geometry analysis, and used it for ego-localization. However, since the method employed a dynamic time warping strategy to avoid the effect from outliers, both input and database images needed to be image sequences. To overcome this problem, the method proposed in this paper reformulates the previous image distance metric to a novel image distance that requires only a single in-vehicle camera image as an input, which is realized by considering the sequential property of the images in the database. We conducted experiments using multiple image sequences captured under various conditions by using an in-vehicle camera mounted on the windshield of a car. The experimental results showed that the proposed method could achieve an accuracy of 89%, and we confirmed its effectiveness.
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