Scene Recognition with Camere Phones for Tourist Information Access
Résumé
Camera phones present new opportunities and challenges for mobile information association and retrieval. The visual input in the real environment is a new and rich interaction modality between a mobile user and vast information base connected to a user�s device via rapidly advancing communication infrastructure. We have developed a system for tourist information access to provide scene description based on an image taken of the scene. In this paper, we describe the working system, the STOIC 101 database, and a new pattern discovery algorithm to learn image patches that are recurrent within a scene class and discriminative across others. We report preliminary scene recognition results on 90 scenes, trained on 5 images per scene, with an accuracy of 92% and 88% on a test set of 110 images, with and without location priming.