The study presented in this paper analyses descriptions extracted with MPEG-7-descriptors from visual content from the statistical point of view. Good descriptors should generate ...
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 ...
In this paper, we propose a graph-based method for fullyautomatic segmentation of the left ventricle and atrium in 3D ultrasound (3DUS) volumes. Our method requires no user input ...
Radford Juang, Elliot R. McVeigh, Beatrice Hoffman...
Abstract. A representation of a three-dimensional object is autonomously learned from a sequence of the rotating object. The representation consists of single views in form of grap...
Gabriele Peters, Christian Eckes, Christoph von de...
⎯This paper presents an improved multi-object segmentation algorithm based on probabilistic labeling. First, a critical look is focused on utilizing vector calculus operator and ...