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...
Physically based dynamic models are able to describe variable shapes without prior training. Their behaviour to find an object is intuitive, which facilitates corrections of false...
In this paper, we present a regularization approach on discrete graph spaces for perceptual image segmentation via semisupervised learning. In this approach, first, a spectral cl...
Relevance feedback is an important mechanism for narrowing the semantic gap in content-based image retrieval and the process involves the user labeling positive and negative images...
We present a new non-parametric model constraint graph min-cut algorithm for automatic kidney segmentation in CT images. The segmentation is formulated as a maximum a-posteriori es...
Moti Freiman, A. Kronman, S. J. Esses, Leo Joskowi...