Representation of local geometry in the visual system
Biological Cybernetics
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boundary Detection by Constrained Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale and the differential structure of images
Image and Vision Computing - Special issue: information processing in medical imaging 1991
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Edge Detection and Ridge Detection with Automatic Scale Selection
International Journal of Computer Vision
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Saliency, Scale and Image Description
International Journal of Computer Vision
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Learning Texture Discrimination Rules in a Multiresolution System
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Scale Selection for Gaussian Based Description Techniques
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Classifier Conditional Posterior Probabilities
SSPR '98/SPR '98 Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Computer Vision and Image Understanding
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Scale Space Approach for Automatically Segmenting Words from Historical Handwritten Documents
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Sparse Texture Representation Using Local Affine Regions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Primal sketch: Integrating structure and texture
Computer Vision and Image Understanding
Supervised texture classification by integration of multiple texture methods and evaluation windows
Image and Vision Computing
Image Segmentation by Pixel Classification in (Gray Level, Edge Value) Space
IEEE Transactions on Computers
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
International Journal of Computer Vision
Maximum Membership Scale Selection
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Quantitative comparison of spot detection methods in live-cell fluorescence microscopy imaging
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Self-Similarity and Points of Interest
IEEE Transactions on Pattern Analysis and Machine Intelligence
A modified support vector machine and its application to image segmentation
Image and Vision Computing
Multiscale conditional random fields for image labeling
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Texture regimes for entropy-based multiscale image analysis
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Maximum likely scale estimation
DSSCV'05 Proceedings of the First international conference on Deep Structure, Singularities, and Computer Vision
Supervised scale-invariant segmentation (and detection)
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Information measures in scale-spaces
IEEE Transactions on Information Theory
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Finding the right scales for feature extraction is crucial for supervised image segmentation based on pixel classification. There are many scale selection methods in the literature; among them the one proposed by Lindeberg is widely used for image structures such as blobs, edges and ridges. Those schemes are usually unsupervised, as they do not take into account the actual segmentation problem at hand. In this paper, we consider the problem of selecting scales, which aims at an optimal discrimination between user-defined classes in the segmentation. We show the deficiency of the classical unsupervised scale selection paradigms and present a supervised alternative. In particular, the so-called max rule is proposed, which selects a scale for each pixel to have the largest confidence in the classification across the scales. In interpreting the classifier as a complex image filter, we can relate our approach back to Lindeberg's original proposal. In the experiments, the max rule is applied to artificial and real-world image segmentation tasks, which is shown to choose the right scales for different problems and lead to better segmentation results.