A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
An Unbiased Detector of Curvilinear Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Saliency, Scale and Image Description
International Journal of Computer Vision
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Towards automatic visual obstacle avoidance
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
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In this paper we present a new approach towards the extraction of affine image regions based on detecting shape-stable boundaries from a multi-scale image representation. We construct an affine morphological scale space (AMSS) representation [1], which performs anisotropic diffusion while preserving boundaries and being invariant to affine transformations. We extract the transition boundaries of the diffusivity velocity map and track their evolution at each level of the scale-space. We then determine the stability of the boundary shape through a minimization process over different scales. Unlike most state of the art detectors which use the Gaussian scale space for multi-scale image representation, our approach is intrinsically affine invariant. We evaluate our detector by measuring repeatability of regions in transformed images of the same scene and comparing it to the state-of-the-art region detectors [2].