PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Pattern recognition with local invariant features
Cordelia Schmid, Gyorgy Dorko, Svetlana Lazebnik, Krystian Mikolajczyk and Jean Ponce
In: Handbook of Pattern Recognition and Computer Vision, 3rd edition (2005) World Scientific Publishing Co. Pte. Ltd , pp. 71-92. ISBN 981-256-105-6

Abstract

Local invariant features have shown to be very successful for recognition. They are robust to occlusion and clutter, distinctive as well as invariant to image transformations. In this chapter recent progress on local invariant features is summarized. It is explained how to extract scale and affine-invariant regions and how to obtain discriminant descriptors for these regions. It is then demonstrated that combining local features with pattern classification techniques allows for texture and category-level object recognition in the presence of varying viewpoints and background clutter.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:426
Deposited By:Gyorgy Dorko
Deposited On:22 December 2004