Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct Least Square Fitting of Ellipses
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Wide Baseline Point Matching Using Affine Invariants Computed from Intensity Profiles
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Affine-Invariant Local Descriptors and Neighborhood Statistics for Texture Recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Object Class Recognition with Many Local Features
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 12 - Volume 12
Scale-invariant shape features for recognition of object categories
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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Affine invariant regions have proved a powerful feature for object recognition and categorization. These features heavily rely on object textures rather than shapes, however. Typically, their shapes have been fixed to ellipses or parallelograms. The paper proposes a novel affine invariant region type, that is built up from a combination of fitted superellipses. These novel features have the advantage of offering a much wider range of shapes through the addition of a very limited number of shape parameters, with the traditional ellipses and parallelograms as subsets. The paper offers a solution for the robust fitting of superellipses to partial contours, which is a crucial step towards the implementation of the novel features.