Paper Info
Title
SKYLINE2GPS: Localization in urban canyons using omni-skylines
Abstract
This paper investigates the problem of geo-localization in GPS challenged urban canyons using only skylines. Our proposed solution takes a sequence of upward facing omnidirectional images and coarse 3D models of cities to compute the geo-trajectory. 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. Under day-time and clear sky conditions, we propose a sky-segmentation algorithm using graph cuts for estimating the geo-location. In cases where the skyline gets affected by partial fog, night-time and occlusions from trees, we propose a shortest path algorithm that computes the location without prior sky detection. We show compelling experimental results for hundreds of images taken in New York, Boston and Tokyo under various weather and lighting conditions (daytime, foggy dawn and night-time).
Year
DOI
Venue
2010
10.1109/IROS.2010.5649105
Intelligent Robots and Systems
Keywords
Field
DocType
Global Positioning System,cameras,computer graphics,image matching,image segmentation,Boston,New York,SKYLINE2GPS,Tokyo,coarse 3D models,geo-localization,geo-trajectory,global position,graph cuts,lighting conditions,occlusions,omni-skylines,sky detection,sky-segmentation algorithm,upward facing omnidirectional images,urban canyons,weather conditions
Skyline,Cut,Computer vision,Computer science,Image segmentation,Sky,Pixel,Global Positioning System,Artificial intelligence,3D city models,Dijkstra's algorithm
Conference
ISSN
ISBN
Citations 
2153-0858
978-1-4244-6674-0
27
PageRank 
References 
Authors
1.05
19
4
Name
Order
Citations
PageRank
Srikumar Ramalingam1271.05
Sofien Bouaziz293435.79
Peter F. Sturm31075.87
Matthew Brand4311.84