With the proliferation of digital video, video summarization and skimming has become an
indispensable tool of any practical video content management system. This paper provides …

We present a multimodal data set for the analysis of human affective states. The
electroencephalogram (EEG) and peripheral physiological signals of 32 participants were …

Video indexing and retrieval have a wide spectrum of promising applications, motivating the
interest of researchers worldwide. This paper offers a tutorial and an overview of the …

This paper investigates the use of automatically extracted visual features of videos in the
context of recommender systems and brings some novel contributions in the domain of …

Affective understanding of film plays an important role in sophisticated movie analysis,
ranking and indexing. However, due to the seemingly inscrutable nature of emotions and the …

As of today, most movie recommendation services base their recommendations on
collaborative filtering (CF) and/or content-based filtering (CBF) models that use metadata …

The task of labeling movies according to their corresponding genre is a challenging
classification problem, having in mind that genre is an immaterial feature that cannot be …

User-generated video collections are expanding rapidly in recent years, and systems for
automatic analysis of these collections are in high demands. While extensive research …

Affective video content analysis has emerged as one of the most challenging and essential
research tasks as it aims to analyze the emotions elicited by videos automatically. However …

With the idea of social network analysis, we propose a novel way to analyze movie videos
from the perspective of social relationships rather than audiovisual features. To …