Street View Challenge: Identification of Commercial Entities in Street View Imagery

Abstract

This paper presents our submission to the Street View Challenge of identifying commercial entities in street view imagery. The provided data set of the challenge consists of approximately 129K street view images tagged with GPScoordinates. The problem is to identify different types of businesses visible in these images. Our solution is based on utilizing the textual information. However, the textual content of street view images is challenging in terms of variety and complexity, which limits the success of the approaches that are purely based on processing the content. Therefore, we use a method which leverages both the textual content of the images and business listings, in order to accomplish the identification task successfully. The robustness of our method is due to the fact that the information obtained from the different resources is cross-validated leading to significant improvements compared to the baselines. The experiments show approximately 70% of success rate on the defined problem.