Predicting geographic location using exclusively the visual content of images holds the promise of greatly benefiting users' access to media collections. In this paper, we present a visual-content-based approach that predicts where in the world a social image was taken. We employ a ranking method that assigns a query photo the geo-location of its most… (More)
Spatial verification is a key step in boosting the performance of object-based image retrieval. It serves to eliminate unreliable correspondences between salient points in a given pair of images, and is typically performed by analyzing the consistency of spatial transformations between the image regions involved in individual correspondences. Spatial… (More)
In this paper, we present a visual-content-based approach that predicts where in the world a social image was tak-en. We employ a ranking method that assigns a query photo the geo-location of its most likely geo-visual neighbor in the social image collection. The experiments carried out on the MediaEval Placing Task 2013 data set support the conclusion that… (More)
In this paper, we describe the ICSI/TU Delft video location estimation system presented at the MediaEval 2014 Placing Task. We describe two text-based approaches based on spatial variance and graphical model framework, a visual-content-based geo-visual ranking approach, and a multi-modal approach that combines the text and visual-based algorithms.
INTRODUCTION On July 1, 2011, the Chinese government launched a national Action Plan for antibiotic stewardship targeting antibiotic misuse in public hospitals. The aim of this study was to evaluate the impacts of the Action Plan in terms of frequency and intensity of antibiotic utilization and patients costs in public general hospitals. METHODS… (More)
Estimating the geo-location of an image or video is an interesting and challenging task in information retrieval and computer vision. In this paper, a pure image content based approach for this task is described. We partition the world map into regions based on external data sources (climate and biomes data). We hypothesize that such a partition yields… (More)
Today's geo-location estimation approaches are able to infer the location of a target image using its visual content alone. These approaches exploit visual matching techniques, applied to a large collection of background images with known geo-locations. Users who are unaware that visual retrieval approaches can compromise their geo-privacy, unwittingly open… (More)
—We propose an image representation and matching approach that substantially improves visual-based location estimation for images. The main novelty of the approach, called distinctive visual element matching (DVEM), is its use of representations that are specific to the query image whose location is being predicted. These representations are based on visual… (More)