Generic Object Recognition in Urban Image Databases

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. All this information is extracted without an object of reference, which allows to search for any type of objects using their visual appearance. A new Visual Content layer is built over Google Maps, allowing the object recognition information to be organized and fused with other content, like satellite images, street maps, and business locations. Keywords. Visual content, object recognition, computer vision.

• Type: Conference
• Year: 2009
• Where: CCIA
• Authors: Xavier Baró, Sergio Escalera, Petia Radeva, Jordi Vitrià
• Keywords: Artificial Intelligence, CCIA 2009, Object Recognition, Visual Appearance, Visual Content Layer