Abstract. Outlier detection is concerned with discovering exceptional behaviors of objects. Its theoretical principle and practical implementation lay a foundation for some importa...
Jian Tang, Zhixiang Chen, Ada Wai-Chee Fu, David W...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
We present Volume dots (Vots), a new primitive for volumetric data modelling, processing, and rendering. Vots are a point-based representation of volumetric data. An individual Vo...
In the past few years, many efficient rendering and surface reconstruction algorithms for point clouds have been developed. However, collision detection of point clouds has not be...
This paper introduces a fast continuous collision detection technique for polyhedral rigid bodies. As opposed to most collision detection techniques, the computation of the first ...