This paper introduces a novel probabilistic activity modeling approach that mines recurrent sequential patterns from documents given as word-time occurrences. In this model, docum...
In this paper, we propose a novel method for the automatic segmentation of a foreground layer from a natural scene in real time by fusing infrared, color and edge information. Thi...
This paper presents a relative depth layer extraction system for monoscopic video, using multi-line filters and a layer selection algorithm. Main ideas are to extract multiple li...
Analysis of video data usually requires training classifiers in high dimensional feature spaces. This paper proposes a layered Gaussian mixture model (LGMM) to exploit high dimens...
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...