Geolocalization using Skylines from Omni-ImagesReport as inadecuate




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1 MERL - Mitsubishi Electric Research Laboratories 2 VRLab - Virtual Reality Lab EPFL 3 PERCEPTION - Interpretation and Modelling of Images and Videos Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble

Abstract : We propose a novel method to accurately estimate the global position of a moving car using an omnidirectional camera and untextured 3D city models. The camera is oriented upwards to capture images of the immediate skyline, which is generally unique and serves as a fingerprint for a specific location in a city. Our goal is to estimate global position by matching skylines extracted from omni-directional images to skyline segments from coarse 3D city models. Our contributions include a sky segmentation algorithm for omni-directional images using graph cuts and a novel approach for matching omni-image skylines to 3D models.





Author: Srikumar Ramalingam - Sofien Bouaziz - Peter Sturm - Matthew Brand -

Source: https://hal.archives-ouvertes.fr/



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