In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...
An ideal shape model should be both invariant to global transformations and robust to local distortions. In this paper we present a new shape modeling framework that achieves both...
This paper presents a new framework for shape modeling and analysis. A shape instance is described by a curvature-based shape descriptor. A Profile Hidden Markov Model (PHMM) is ...
We present a novel framework based on hidden Markov models (HMMs) for matching feature point sets, which capture the shapes of object contours of interest. Point matching algorith...
Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent,...
Stefan Mutter, Bernhard Pfahringer, Geoffrey Holme...