Arman Savran

TL;DR: A new 3D face database that includes a rich set of expressions, systematic variation of poses and different types of occlusions is presented, which can be a very valuable resource for development and evaluation of algorithms on face recognition under adverse conditions and facial expression analysis as well as for facial expression synthesis.

TL;DR: A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented, comprised of more than 600 individuals acquired simultaneously in three scenarios: over the Internet, in an office environment with desktop PC, and in indoor/outdoor environments with mobile portable hardware.

TL;DR: This work proposes a novel AU intensity estimation scheme applied to 2D luminance and/or 3D surface geometry images and performs significantly better than the state-of-the-art method which is based on the margins of SVMs designed for AU detection.

TL;DR: Besides the techniques mentioned above, peripheral signals, namely, respiration, cardiac rate, and galvanic skin resistance were also measured from the subjects during “fNIRS + EEG” recordings, which provided us with extra information about the emotional state of the subjects.

TL;DR: A comparative evaluation of 3D and 2D face modalities is conducted and it is demonstrated that overall 3D data performs better, especially for lower face AUs and that there is room for improvement by fusion of 2D and 3D modalities.