1. What Makes Paris Look Like Paris?
- Author
-
Doersch, Carl, Singh, Saurabh, Gupta, Abhinav, Sivic, Josef, and Efros, Alexei A.
- Subjects
- *
IMAGE processing software , *IMAGE recognition (Computer vision) , *ARCHITECTURAL details , *GEOGRAPHY software ,PARIS (France) description & travel - Abstract
Given a large repository of geo-tagged imagery, we seek to automatically find visual elements, for example windows, balconies, and street signs, that are most distinctive for a certain geo-spatial area, for example the city of Paris. This is a tremendously difficult task as the visual features distinguishing architectural elements of different places can be very subtle. In addition, we face a hard search problem: given all possible patches in all images, which of them are both frequently occurring and geographically informative? To address these issues, we propose to use a discriminative clustering approach able to take into account the weak geographic supervision. We show that geographically representative image elements can be discovered automatically from Google Street View imagery in a discriminative manner. We demonstrate that these elements are visually interpretable and perceptually geo-informative. The discovered visual elements can also support a variety of computational geography tasks, such as mapping architectural correspondences and influences within and across cities, finding representative elements at different geo-spatial scales, and geographically informed image retrieval. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
- View/download PDF