Daniel Reisfeld

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Active vision systems, and especially foveated vision systems, depend on efficient attentional mechanisms. We propose that machine visual attention should consist of both high-level, context-dependent components, and low-level, context free components. As a basis for the context-free component, we present an attention operator based on the intuitive notion(More)
The human face is an elastic object. A natural paradigm for representing facial expressions is to form a complete 3D model of facial muscles and tissues. However, determining the actual parameter values for synthesizing and animating facial expressions is tedious; evaluating these parameters for facial expression analysis out of grey-level images is ahead(More)
A system for automatic face recognition is presented. It consists of several steps. Automatic detection of the eyes and mouth is followed by a spatial normalization of the images. The classification of the normalized images is carried out by a hybrid (supervised and unsupervised) Neural Network. Two methods for reducing the overfitting a common problem in(More)
Symmetry is one of the most prominent cues in visual perception as well as in computer vision. We have recently presented a Generalized Symmetry Transform that receives as input an edge map, and outputs a symmetry map, where every point marks the intensity and orientation of the local generalized symmetry. In the context of computer vision, this map(More)
Exposure to low levels of ionizing radiation after the Chernobyl accident in the Ukraine could potentially have influenced the neurobehavioral and cognitive performances of exposed children. A cohort study of adolescents who were children at the time of the accident and who subsequently emigrated to Israel was conducted in 1998-2001. A total of 1,629(More)