International Journal of Computer Vision
The nature of statistical learning theory
The nature of statistical learning theory
Support Vector Machines for 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
A Trainable System for Object Detection
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hausdorff Kernel for 3D Object Acquisition and Detection
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
General Purpose Matching of Grey Level Arbitrary Images
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Indoor-Outdoor Image Classification
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Learning Support Vectors for Face Verification and Recognition
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Face Recognition by Support Vector Machines
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
A Hidden Markov Model approach for appearance-based 3D object recognition
Pattern Recognition Letters
Grayscale medical image annotation using local relational features
Pattern Recognition Letters
A novel robust kernel for visual learning problems
Neurocomputing
Content-based histopathology image retrieval using a kernel-based semantic annotation framework
Journal of Biomedical Informatics
PHOG-derived aesthetic measures applied to color photographs of artworks, natural scenes and objects
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
How self-similar are artworks at different levels of spatial resolution?
Proceedings of the Symposium on Computational Aesthetics
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In this paper we discuss the mathematical properties of a few kernels specifically constructed for dealing with image data in binary classification and novelty detection problems. First, we show that histogram intersection is a Mercer's kernel. Then, we show that a similarity measure based on the notion of Hausdorff distance and directly applicable to raw images, though not a Mercer's kernel, is a kernel for novelty detection. Both kernels appear to be well suited for building effective vision-based learning systems.