Abstract. In this paper we propose a new distance metric for probability density functions (PDF). The main advantage of this metric is that unlike the popular Kullback-Liebler (KL)...
In this paper we describe and analyze a method based on local least square fitting for estimating the normals at all sample points of a point cloud data (PCD) set, in the presenc...
Bayesian statistical theory is a convenient way of taking a priori information into consideration when inference is made from images. In Bayesian image detection, the a priori dist...
This paper is concerned with the e cient reconstruction of illumination from area luminaires. We outline a 2-pass scheme a lightpass, tracing ray bundles from the luminaires follow...
Developing a visually convincing model of fire, smoke, and other gaseousphenomenais among the most difficult and attractive problems in computer graphics. We have created new me...