Jet based feature classification

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

We investigate to which extent the "raw" mapping of Taylor series coefficients into jet-space can be used as a "language" for describing local image structure in terms of geometrical image features. Based on empirical data from the van Hateren database, we discuss modelling of probability densities for different feature types, calculate feature posterior maps, and finally perform classification or simultaneous feature detection in a Bayesian framework. We introduce the Brownian image model as a generic background class and extend with empirically estimated densities for edges and blobs. We give examples of simultaneous feature detection across scale.
Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, 2004 : ICPR 2004
Number of pages4
Publication date2004
ISBN (Print)0-7695-2128-2
Publication statusPublished - 2004
Externally publishedYes
Event17th International Conference on Pattern Recognition - Cambridge, United Kingdom
Duration: 23 Aug 200426 Aug 2004
Conference number: 17


Conference17th International Conference on Pattern Recognition
LandUnited Kingdom

ID: 5520639