Semantic Scholar Open Access 2008 1033 sitasi

IM2GPS: estimating geographic information from a single image

James Hays Alexei A. Efros

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Abstrak

Estimating geographic information from an image is an excellent, difficult high-level computer vision problem whose time has come. The emergence of vast amounts of geographically-calibrated image data is a great reason for computer vision to start looking globally - on the scale of the entire planet! In this paper, we propose a simple algorithm for estimating a distribution over geographic locations from a single image using a purely data-driven scene matching approach. For this task, we leverage a dataset of over 6 million GPS-tagged images from the Internet. We represent the estimated image location as a probability distribution over the Earthpsilas surface. We quantitatively evaluate our approach in several geolocation tasks and demonstrate encouraging performance (up to 30 times better than chance). We show that geolocation estimates can provide the basis for numerous other image understanding tasks such as population density estimation, land cover estimation or urban/rural classification.

Topik & Kata Kunci

Computer Science Geography

Penulis (2)

James Hays

Alexei A. Efros

Format Sitasi

APA MLA BibTeX

Hays, J., Efros, A.A. (2008). IM2GPS: estimating geographic information from a single image. https://doi.org/10.1109/CVPR.2008.4587784

Akses Cepat

Lihat di Sumber doi.org/10.1109/CVPR.2008.4587784

Informasi Jurnal

Tahun Terbit: 2008
Bahasa: en
Total Sitasi: 1033×
Sumber Database: Semantic Scholar
DOI: 10.1109/CVPR.2008.4587784
Akses: Open Access ✓