We present a novel method for incorporating prior knowledge about invariances in object recognition for discriminant analysis. In contrast to conventional isotropic regularization...
We present a new approach for the identification and segmentation of objects undergoing periodic motion. Our method uses a combination of maximum likelihood estimation of the per...
In this work we introduce a probabilistic model for classifying segmented images. The proposed classifier is very general and it can deal both with images that were segmented wit...
Biometrics based on electroencephalogram (EEG) signals is an emerging research topic. Several recent results have shown its feasibility and potential for personal identification....
This paper presents a novel feature set for visual tracking that is derived from “oriented energies”. More specifically, energy measures are used to capture a target’s multi...