Abstract—Choosing the right feature for motion based activity spotting is not a trivial task. Often, features derived by intuition or that proved to work well in previous work ar...
Ulf Blanke, Bernt Schiele, Matthias Kreil, Paul Lu...
Face recognition (FR) is an active yet challenging topic in computer vision applications. As a powerful tool to represent high dimensional data, recently sparse representation bas...
— Simulated Evolution (SimE) is a sound stochastic approximation algorithm based on the principles of adaptation. If properly engineered it is possible for SimE to reach nearopti...
Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....
Many state-of-the-art face recognition algorithms use image descriptors based on features known as Local Binary Patterns (LBPs). While many variations of LBP exist, so far none of ...