Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Visual Modeling with a Hand-Held Camera
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Wide-baseline multiple-view correspondences
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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Given a set of unordered images taken in a wide area, an effective solution is proposed for establishing robust feature correspondences among them. Two major improvements are made in our work as follows: firstly, a robust technique is proposed for the self-organization of a large number of images without spatial orderings; secondly, a novel wide-baseline matching approach is developed to obtain good correspondences over images taken from substantially different viewpoints. The output consists of many sets of reliable pair-wise feature correspondences which are essential in various computer vision applications. Realistic experiments were carried out to evaluate the performances of the proposed method by using a large amount of images captured from our university's campus.