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Street View And Fancy Algorithms.pdf

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Preview of street view and fancy algorithms
🔗 Source: graphics.cs.cmu.edu
📊 Size: 8.09 MB
📄 Pages: 9 pages
⬇️ Downloads: 332

Summary

Researchers from Carnegie Mellon University and INRIA/Ecole Normale Supérieure propose an algorithm to automatically discover visual elements that are distinctive for a certain geographic area, such as the city of Paris. Given a large database of geotagged images, the algorithm identifies repeating and geographically discriminative elements, like windows, balconies, and street signs, that are unique to a particular city. The discovered elements can support various computational geography tasks, including mapping architectural correspondences and influences, finding representative elements, and geographically-informed image retrieval. The work aims to understand which visual elements are fundamental to our perception of a complex visual concept, such as a place, and has potential applications in computer graphics, reference art generation, and computational geo-cultural modeling.

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Description

Researchers from Carnegie Mellon University and INRIA/Ecole Normale Supérieure propose an algorithm to automatically discover visual elements that are...

Technical Information

  • File Format: PDF
  • File Size: 8.09 MB
  • Pages: 9
  • Language: EN
  • Total Downloads: 332
  • Last Updated: 3 weeks ago

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