BCN Perceptual Computing Lab Repository

Visual Content Layer for Scalable Object Recognition in Urban Image Databases

Baró, Xavier and Escalera, Sergio and Radeva, Petia and Vitrià, Jordi (2009) Visual Content Layer for Scalable Object Recognition in Urban Image Databases. To Appear . (Unpublished)

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Abstract

Rich online map interaction represents a useful tool to get multimedia information related to physical places. With this type of systems, users can automatically compute the optimal route for a trip or to look for entertainment places or hotels near their actual position. Standard maps are defined as a fusion of layers, where each one contains specific data such height, streets, or a particular business location. In this paper we propose the construction of a visual content layer which describes the visual appearance of geographic locations in a city. We captured, by means of a Mobile Mapping system, a huge set of georeferenced images (> 500K) which cover the whole city of Barcelona. For each image, hundreds of region descriptions are computed off-line and described as a hash code. This allows an efficient and scalable way of accessing maps by visual content.

Item Type:Article
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
ID Code:18
Deposited By:Xavier Baró
Deposited On:12 Jun 2009 19:35
Last Modified:29 Nov 2010 17:52

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