Fundamentals of digital image processing
Fundamentals of digital image processing
Artificial Intelligence - Special volume on computer vision
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Visual Homing: Surfing on the Epipoles
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Comparing and Evaluating Interest Points
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Combining Appearance and Topology for Wide Baseline Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Vision-Based Multi-Robot Simultaneous Localization and Mapping
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Unsupervised facade segmentation using repetitive patterns
Proceedings of the 32nd DAGM conference on Pattern recognition
Wide-baseline multiple-view correspondences
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Keygraphs for sign detection in indoor environments by mobile phones
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
Towards reliable matching of images containing repetitive patterns
Pattern Recognition Letters
A shape based, viewpoint invariant local descriptor
MLMI'04 Proceedings of the First international conference on Machine Learning for Multimodal Interaction
A robust image retrieval system for mobile guide applications
International Journal of Intelligent Systems
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The problem of establishing correspondences between images taken from different viewpoints is fundamental in computer vision. We propose an algorithm which is capable of handling larger changes in viewpoint than classical correlation based techniques. Optimal performance for the algorithm is achieved for textured objects which are locally planar in at least one direction. The algorithm works by computing affinely invariant fourier features from intensity profiles in each image. The intensity profiles are extracted from the image data between randomly selected pairs of image interest points. Using a voting scheme, pairs of interest points are matched across images by comparing vectors of fourier features. Outliers among the matches are rejected in two stages, a fast stage using novel view consistency constraints, and a second, slower stage using RANSAC and fundamental matrix computation. In order to demonstrate the quality of the results, the algorithm is tested on several different image pairs.