Computer Vision
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Automated event clustering and quality screening of consumer pictures for digital albuming
IEEE Transactions on Multimedia
Multimedia Tools and Applications
Content-Based Keyframe Clustering Using Near Duplicate Keyframe Identification
International Journal of Multimedia Data Engineering & Management
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The explosion in use of digital visual media has created many challenges for efficient search and retrieval of relevant content from large consumer photo collections. This paper proposes a novel approach to reliably retrieve photos taken at a particular location, that can also be used to narrow the search space when used in conjunction with other search dimensions such as date, event, and people present in images. By using a novel clustering algorithm with intelligent filtering steps, consumer images with cluttered background and common objects can be matched effectively. A major contribution of the paper is to present a set of constraints that produce reliable matching with high precision between two images. The other important contribution is to combine this scene matching technique with automatically computed temporal event clustering to provide a solution for location clustering of events in consumer image collections. We have developed a software application to evaluate the performance of this method using actual consumer images. Experimental results have shown that this approach produces scene matches with high precision that can be used to aid the tagging of events with location.