Markov random field (MRF) theory has widely been applied to segmentation in noisy images. This paper proposes a new MRF method. First, it couples the original labeling MRF with a ...
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Within this paper a new framework for Bayesian tracking is presented, which approximates the posterior distribution at multiple resolutions. We propose a tree-based representation...
Bjoern Stenger, Arasanathan Thayananthan, Philip H...
We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure" model. The 3D shape of an object class is represented by sets...
Kristen Grauman, Gregory Shakhnarovich, Trevor Dar...
We describe a new approach for evaluating page segmentation algorithms. Unlike techniques that rely on OCR output, our method is region-based: the segmentation output, described a...