In this work we present a novel approach for learning nonhomogenous textures without facing the unlearning problem. Our learning method mimics the human behavior of selective lear...
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
Abstract. Motion segmentation methods often fail to detect the motions of low textured regions. We develop an algorithm for segmentation of low textured moving objects. While usual...
In this paper, the task of text segmentation is approached from a topic modeling perspective. We investigate the use of latent Dirichlet allocation (LDA) topic model to segment a ...
Text segmentation is important for text analysis, while text alignment is to determine shared sub-topics among similar documents. Multi-task text segmentation and alignment is the...