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ECCV
2010
Springer

Location Recognition Using Prioritized Feature Matching

9 years 29 days ago
Location Recognition Using Prioritized Feature Matching
We present a fast, simple location recognition and image localization method that leverages feature correspondence and geometry estimated from large Internet photo collections. Such recovered structure contains a significant amount of useful information about images and image features that is not available when considering images in isolation. For instance, we can predict which views will be the most common, which feature points in a scene are most reliable, and which features in the scene tend to co-occur in the same image. Based on this information, we devise an adaptive, prioritized algorithm for matching a representative set of SIFT features covering a large scene to a query image for efficient localization. Our approach is based on considering features in the scene database, and matching them to query image features, as opposed to more conventional methods that match image features to visual words or database features. We find this approach results in improved performance, due to ...
Yunpeng Li, Noah Snavely, Daniel P. Huttenlocher
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2010
Where ECCV
Authors Yunpeng Li, Noah Snavely, Daniel P. Huttenlocher
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