Title

Accurate Image Localization Based On Google Maps Street View

Abstract

Finding an image's exact GPS location is a challenging computer vision problem that has many real-world applications. In this paper, we address the problem of finding the GPS location of images with an accuracy which is comparable to hand-held GPS devices.We leverage a structured data set of about 100,000 images build from Google Maps Street View as the reference images. We propose a localization method in which the SIFT descriptors of the detected SIFT interest points in the reference images are indexed using a tree. In order to localize a query image, the tree is queried using the detected SIFT descriptors in the query image. A novel GPS-tag-based pruning method removes the less reliable descriptors. Then, a smoothing step with an associated voting scheme is utilized; this allows each query descriptor to vote for the location its nearest neighbor belongs to, in order to accurately localize the query image. A parameter called Confidence of Localization which is based on the Kurtosis of the distribution of votes is defined to determine how reliable the localization of a particular image is. In addition, we propose a novel approach to localize groups of images accurately in a hierarchical manner. First, each image is localized individually; then, the rest of the images in the group are matched against images in the neighboring area of the found first match. The final location is determined based on the Confidence of Localization parameter. The proposed image group localization method can deal with very unclear queries which are not capable of being geolocated individually. © 2010 Springer-Verlag.

Publication Date

1-1-2010

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

6314 LNCS

Issue

PART 4

Number of Pages

255-268

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-642-15561-1_19

Socpus ID

78149346965 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/78149346965

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