Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
International Journal of Computer Vision
Multi-view Matching for Unordered Image Sets, or "How Do I Organize My Holiday Snaps?"
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Hierarchical building recognition
Image and Vision Computing
An Improved Shock Graph Approach for Shape Recognition and Retrieval
AMS '07 Proceedings of the First Asia International Conference on Modelling & Simulation
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This paper describes an approach to recognize building surfaces. A building image is analyzed to extract the natural characters such as the surfaces and their areas, vanishing points, wall region and a list of SIFT feature vectors. These characters are organized as a hierarchical system of features to describe a model of building and then stored in a database. Given a new image, the characters are computed in the same form with in database. Then the new image is compared against the database to choose the best candidate. A cross ratio based algorithm, a novel approach, is used to verify the correct match. Finally, the correct match is used to update the model of building. The experiments show that the approach method clearly decreases the size of database, obtains high recognition rate. Furthermore, the problem of multiple buildings can be solved by separately analyzing each surface of building.