We present a new scheme to robustly detect a type of human attentive behavior, which we call frequent change in focus of attention (FCFA), from video sequences. FCFA behavior can b...
This paper presents an unsupervised learning approach to video-based face recognition that does not make any assumptions about the pose, expressions or prior localization of landm...
In this paper, on-line training of neural networks is investigated in the context of computer-assisted colonoscopic diagnosis. A memory-based adaptation of the learning rate for t...
George D. Magoulas, Vassilis P. Plagianakos, Micha...
Advances in computer vision and pattern recognition research are leading to video surveillance systems with improved scene analysis capabilities. However, up to now few works have ...
Alessio Dore, Matteo Pinasco, Lorenzo Ciardelli, C...
Object/scene detection by discriminative kernel-based classification has gained great interest due to its promising performance and flexibility. In this paper, unlike traditional ...