“Image Ranking with Density Trees for Google Maps” by Johnson and Berkiten
Conference:
Type(s):
Entry Number: 42
Title:
- Image Ranking with Density Trees for Google Maps
Presenter(s)/Author(s):
Abstract:
We propose an unsupervised learning technique for image ranking of photos contributed by Google Maps users. A density tree is built for each point-of-interest (POI), such as The National Mall or the Louvre. This tree is used to construct clusters, which are then ranked based on size and quality. We choose a representative image for each cluster, resulting in a ranked set of high-quality, diverse, and relevant images for each POI. We validated our algorithm in a side-by-side preference study.
References:
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