Video scene analysis is a recent research topic due to its vital importance in many
applications such as real-time vehicle activity tracking, pedestrian detection, surveillance …

Multimodal recognition of affective states is a difficult problem, unless the recording
conditions are carefully controlled. For recognition “in the wild”, large variances in face pose …

A key challenge of facial expression recognition (FER) is to develop effective
representations to balance the complex distribution of intra-and inter-class variations. The …

Video based facial expression recognition has been a long standing problem and attracted
growing attention recently. The key to a successful facial expression recognition system is to …

Many factors render multimodal affect recognition approaches appealing. First, humans
employ a multimodal approach in emotion recognition. It is only fitting that machines, which …

The computer vision literature shows that randomly weighted neural networks perform
reasonably as feature extractors. Following this idea, we study how non-trained (randomly …

An ensemble visual-audio emotion recognition framework is proposed based on multi-task
and blending learning with multiple features in this paper. To solve the problem that existing …

With the increasing presence of online social networks (OSN), there is a growing interest in
accurately predicting user behaviors based on the data collected from OSN. Unlike …

An important research direction in speech technology is robust cross-corpus and cross-
language emotion recognition. In this paper, we propose computationally efficient and …

In this article, we present the first child emotional speech corpus in Russian, called
“EmoChildRu”, collected from 3 to 7 years old children. The base corpus includes over 20 K …