Stefanos Zafeiriou

TL;DR: The Imperial College London, Technische Universitat Munchen and University of Passau team approach to the MediaEval's "Affective Impact of Movies" challenge, which consists in the automatic detection of affective and violent content in movie excerpts, is described.

TL;DR: It is shown that when fuzzy C-means (FCM) algorithm is used in an over-partitioning mode, the resulting membership values can be further utilized for building a connectivity graph that represents the relative distribution of the computed centroids.

TL;DR: In this paper, the authors presented the most complete 3DMM of the human head to date that includes face, cranium, ears, eyes, teeth and tongue, and used the Gaussian Process framework to blend covariance matrices from multiple models.

TL;DR: The Unconstrained Ear Recognition Challenge (UERC) as mentioned in this paper was a group benchmarking effort centered around the problem of person recognition from ear images captured in uncontrolled conditions, where the goal was to assess the performance of existing ear recognition techniques on a challenging large-scale dataset and identify open problems that need to be addressed in the future.

TL;DR: This chapter aims at highlighting the differences between real-world and laboratory settings, describing emotions for audio and video-based recognition, and presenting the current state of the affective computing community.