Abstract
Obtaining an accurate vehicle position is important for intelligent vehicles in supporting driver safety and comfort. This paper proposes an accurate ego-localization method by matching in-vehicle camera images to an aerial image. There are two major problems in performing an accurate matching: (1) image difference between the aerial image and the in-vehicle camera image due to view-point and illumination conditions, and (2) occlusions in the in-vehicle camera image. To solve the first problem, we use the SURF image descriptor, which achieves robust feature-point matching for the various image differences. Additionally, we extract appropriate feature-points from each road-marking region on the road plane in both images. For the second problem, we utilize sequential multiple in-vehicle camera frames in the matching. The experimental results demonstrate that the proposed method improves both ego-localization accuracy and stability.
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Noda, M. et al. (2011). Vehicle Ego-Localization by Matching In-Vehicle Camera Images to an Aerial Image. In: Koch, R., Huang, F. (eds) Computer Vision – ACCV 2010 Workshops. ACCV 2010. Lecture Notes in Computer Science, vol 6469. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22819-3_17
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DOI: https://doi.org/10.1007/978-3-642-22819-3_17
Publisher Name: Springer, Berlin, Heidelberg
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