We present a system for virtual mirror experience that performs attentive facial geometric alterations in augmented reality. The virtual mirror is simulated using commonly available PC with webcam that capture, process and display video in real-time. High realism is obtained by considerate 3D-aware warping of the 2D captured video. A Kalman-based real-time face tracker is used for 3D head pose estimation and accurate facial features localization. The 3D face model used is adapted to the person in front of the mirror by utilizing active shape models for facial landmarks detection, followed by z-depth progressive refining. Geometric adjustments are performed on 3D face vertices while the 2D warping is calculated utilizing the location of back-projected-to-2D face model vertices. The evaluation of our system shows that realistic facial modifications can be rendered in scenarios that correspond to typical usage of a real mirror.

The Huawei/3DLife Grand Challenge Dataset provides multimodal recordings of Salsa dancing, consisting of audiovisual streams along with depth maps and inertial measurements. In this paper, we propose a system for augmented reality-based evaluations of Salsa dancer performances. An essential step for such a system is the automatic temporal synchronisation of the multiple modalities captured from different sensors, for which we propose efficient solutions. Furthermore, we contribute modules for the automatic analysis of dance performances and present an original software application, specifically designed for the evaluation scenario considered, which enables an enhanced dance visualisation experience, through the augmentation of the original media with the results of our automatic analyses.