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A Trainable Low-level Feature Detector


Reference:

Hall, P. M., Owen, M. J. and Collomosse, J. P., 2004. A Trainable Low-level Feature Detector. In: Proceedings Intl. Conference on Pattern Recognition (ICPR), 2004-08-01.

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Abstract

We introduce a trainable system that simultaneously filters and classifies low-level features into types specified by the user. The system operates over full colour images, and outputs a vector at each pixel indicating the probability that the pixel belongs to each feature type. We explain how common features such as edge, corner, and ridge can all be detected within a single framework, and how we combine these detectors using simple probability theory. We show its efficacy, using stereo-matching as an example.

Details

Item Type Conference or Workshop Items (Paper)
CreatorsHall, P. M., Owen, M. J. and Collomosse, J. P.
DepartmentsFaculty of Science > Computer Science
RefereedNo
StatusPublished
ID Code5478

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