We present a new class of deformable models, MetaMorphs, whose formulation integrates both shape and interior texture. The model deformations are derived from both boundary and re...
This paper studies image alignment, the problem of learning a shape and appearance model from labeled data and efficiently fitting the model to a non-rigid object with large varia...
Xiaoming Liu 0002, Ting Yu, Thomas Sebastian, Pete...
A neural architecture is presented that encodes the visual space inside and outside of a shape. The contours of a shape are propagated across an excitable neuronal map and fed thro...
Statistical shape analysis has become of increasing interest to the neuroimaging community due to its potential to precisely locate morphological changes and thus potentially discr...
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...