Hasil untuk "Geography"

A. Peterson, Jorge Soberón, R. Pearson et al.

A. Roy

Brian F. Cooper, R. Ramakrishnan, U. Srivastava et al.

James Hays, Alexei A. Efros

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.

D. Schmitt, J. Allik, R. McCrae et al.

D. Barker, C. Osmond, J. Golding et al.

G. Bonham-Carter

M. Dybdahl

Telmo Menezes, Camille Roth

Human mobility is known to be distributed across several orders of magnitude of physical distances, which makes it generally difficult to endogenously find or define typical and meaningful scales. Relevant analyses, from movements to geographical partitions, seem to be relative to some ad-hoc scale, or no scale at all. Relying on geotagged data collected from photo-sharing social media, we apply community detection to movement networks constrained by increasing percentiles of the distance distribution. Using a simple parameter-free discontinuity detection algorithm, we discover clear phase transitions in the community partition space. The detection of these phases constitutes the first objective method of characterising endogenous, natural scales of human movement. Our study covers nine regions, ranging from cities to countries of various sizes and a transnational area. For all regions, the number of natural scales is remarkably low (2 or 3). Further, our results hint at scale-related behaviours rather than scale-related users. The partitions of the natural scales allow us to draw discrete multi-scale geographical boundaries, potentially capable of providing key insights in fields such as epidemiology or cultural contagion where the introduction of spatial boundaries is pivotal.

J. Thompson

G. C. Stevens

D. Chelton, R. Deszoeke, M. Schlax et al.

J. MacLaughlin

D. O'Sullivan, D. Unwin

Samuel W. Bodman

A. Gentry

N. Brenner

P. Maskell

W. Hoefsloot, J. van Ingen, C. Andrejak et al.

Hansi Senaratne, A. Mobasheri, A. Ali et al.