SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Robust Image Corner Detection Through Curvature Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Matching Widely Separated Views Based on Affine Invariant Regions
International Journal of Computer Vision
Scale & Affine Invariant Interest Point Detectors
International Journal of 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
Techniques for efficient and effective transformed image identification
Journal of Visual Communication and Image Representation
Performance evaluation of corner detectors using consistency and accuracy measures
Computer Vision and Image Understanding
PCA-SIFT: a more distinctive representation for local image descriptors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Robust Image Corner Detection Based on the Chord-to-Point Distance Accumulation Technique
IEEE Transactions on Multimedia
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To achieve scale-invariance, the approach used by many corner detection and description methods is to derive an appropriate scale as part of the process of detecting each corner and then use this scale for estimating region(s) around the corner to build the descriptor(s). However, this approach is not suitable for methods that do not derive such scale information in their corner detection process. This paper proposes a new method for selecting regions around a corner so that descriptors, which are invariant to scale changes and other image transformations, can be built to represent the corner. Our experimental results show that our proposed method achieves better precision-and-recall results than existing methods.