We propose a new loss function for discriminative learning of Markov random fields, which is an intermediate loss function between the sequential loss and the pointwise loss. We s...
This paper presents an event detector for emergencies in crowds. Assuming a single camera and a dense crowd we rely on optical flow instead of tracking statistics as a feature to ...
Ernesto L. Andrade, Scott Blunsden, Robert B. Fish...
This paper presents a novel algorithm for unsupervised texture segmentation. The proposed algorithm incorporates the Local Binary Pattern operator under a segmentation framework b...
Dimitrios E. Maroulis, Dimitrios K. Iakovidis, Mic...
A measure of stability for a wide class of pattern recognition algorithms is introduced to cope with overfitting in classification problems. Based on this concept, constructive me...
In this work, two new techniques for non-linear feature extraction are presented. In these techniques, new features are obtained as radial projections of the original measurements...