The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
Abstract In many problems from different disciplines such as engineering, physics, medicine, and biology, a series of experimental data is used in order to generate a model that ca...
Georges K. Saharidis, Ioannis P. Androulakis, Mari...
For many years, object tracking in images has suffered from the problems of occlusions and illumination effects. In order to resolve occlusion problems, we have been proposing the...
In this paper, we present an approach based on 2D slices for measuring similarity between 3D models. The key idea is to represent the 3D model by a series of slices along certain ...
Jiantao Pu, Yi Liu, Guyu Xin, Hongbin Zha, Weibin ...