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What makes Paris look like Paris?

Doersch, Carl ; Singh, Saurabh ; Gupta, Abhinav ; Sivic, Josef ; Efros, Alexei A.

ACM transactions on graphics, 2015-12, Vol.58 (12), p.103-110 [Periódico revisado por pares]

New York: Association for Computing Machinery

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  • Título:
    What makes Paris look like Paris?
  • Autor: Doersch, Carl ; Singh, Saurabh ; Gupta, Abhinav ; Sivic, Josef ; Efros, Alexei A.
  • Assuntos: Balconies ; Cartography ; Cities ; Clustering ; Computer Science ; Computer Vision and Pattern Recognition ; Geographic information systems ; Geography ; Image management ; Image retrieval ; Mapping ; Spatial data ; Studies ; Traffic signs ; Visual tasks
  • É parte de: ACM transactions on graphics, 2015-12, Vol.58 (12), p.103-110
  • Descrição: 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.
  • Editor: New York: Association for Computing Machinery
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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