Planar structure matching under projective uncertainty for geolocation

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Abstract

Image based geolocation aims to answer the question: where was this ground photograph taken? We present an approach to geolocalating a single image based on matching human delineated line segments in the ground image to automatically detected line segments in ortho images. Our approach is based on distance transform matching. By observing that the uncertainty of line segments is non-linearly amplified by projective transformations, we develop an uncertainty based representation and incorporate it into a geometric matching framework. We show that our approach is able to rule out a considerable portion of false candidate regions even in a database composed of geographic areas with similar visual appearances. © 2014 Springer International Publishing.

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Li, A., Morariu, V. I., & Davis, L. S. (2014). Planar structure matching under projective uncertainty for geolocation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8695 LNCS, pp. 265–280). Springer Verlag. https://doi.org/10.1007/978-3-319-10584-0_18

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