2015 Volume 67 Issue 2 Pages 105-111
In recent years, by the spread of sharing services of images and videos, we have come to be able to acquire images and photographs of several cities in the world from the Internet. This information can expect to apply to the three-dimensional model generation of the city and the frequent update of the map or scene simulation, but may cause the presentation of the wrong information when the data of various cities mingles. On the other hand, many researchers try to take the information that a human being perceives out of the information about the scene and study on labeling of the scene, but there are few successful methods to identify images taken from plural cities. Therefore, we aim for the global localization of images which are taken at various cities in the world. In the method, we introduce random forest to learn the information of each city from a street view image, then estimate the city where an inputted image taken from. We proved it using images acquired from 15cities to confirm the effectiveness of the technique.
