In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
We formulate the problem of salient region detection in images as Markov random walks performed on images represented as graphs. While the global properties of the image are extra...
This paper presents a novel two-phase stereo matching algorithm using the random walks framework. At first, a set of reliable matching pixels is extracted with prior matrices de...
This paper presents a dynamic conditional random field (DCRF) model to integrate contextual constraints for object segmentation in image sequences. Spatial and temporal dependenci...
We propose a new objective function for superpixel segmentation. This objective function consists of two components: entropy rate of a random walk on a graph and a balancing term....