This paper develops a weakly supervised algorithm that learns to segment rigid multi-colored objects from a set of training images and key points. The approach uses congealing to ...
Douglas Moore, John Stevens, Scott Lundberg, Bruce...
: Medical image segmentation often involves variants of deformable models to account for both the variability of object shapes and variation in image quality. Segmentation quality,...
A volumetric image segmentation algorithm has been developed and implemented by extending a 2D algorithm based on Active Shape Models. The new technique allows segmentation of 3D ...
Molly M. Dickens, Shaun S. Gleason, Hamed Sari-Sar...
In the present paper, we address the problem of recovering the true underlying model of a surface while performing the segmentation. A novel criterion for surface (model) selection...
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...