We present a variational integration of nonlinear shape statistics into a Mumford?Shah based segmentation process. The nonlinear statistics are derived from a set of training silho...
Can a machine learn to perceive emotions as evoked by an artwork? Here we propose an emotion categorization system, trained by ground truth from psychology studies. The training d...
Victoria Yanulevskaya, Jan van Gemert, Katharina R...
We propose a new framework for multi-object segmentation of deep brain structures, which have significant shape variations and relatively small sizes in medical brain images. In th...
We achieve two goals in this paper: (1) to build a novel appearance-based object representation that takes into account variations in contrast often found in training images; (2) ...
Chakra Chennubhotla, Allan D. Jepson, John Midgley
Active Shape Models (ASM) have proven to be an effective approach for image segmentation. In some applications, however, the linear model of gray level appearance around a contour ...
Marleen de Bruijne, Bram van Ginneken, Max A. Vier...