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ECCV
2002
Springer
14 years 6 months ago
An Affine Invariant Interest Point Detector
This paper presents a novel approach for detecting affine invariant interest points. Our method can deal with significant affine transformations including large scale changes. Such...
Krystian Mikolajczyk, Cordelia Schmid
ECCV
2006
Springer
14 years 6 months ago
Maximally Stable Local Description for Scale Selection
Scale and affine-invariant local features have shown excellent performance in image matching, object and texture recognition. This paper optimizes keypoint detection to achieve sta...
Cordelia Schmid, Gyuri Dorkó
ICCV
2001
IEEE
14 years 6 months ago
Indexing Based on Scale Invariant Interest Points
This paper presents a new method for detecting scale invariant interest points. The method is based on two recent results on scale space: 1) Interest points can be adapted to scal...
Krystian Mikolajczyk, Cordelia Schmid
ECCV
2004
Springer
14 years 6 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
ECCV
2010
Springer
13 years 9 months ago
Critical Nets and Beta-Stable Features for Image Matching
Abstract. We propose new ideas and efficient algorithms towards bridging the gap between bag-of-features and constellation descriptors for image matching. Specifically, we show ho...