Automatic emotion recognition is the process of identifying human emotion from signals
such as facial expression, speech, and text. Collecting and labeling such signals is often …

Gesture recognition aims to recognize meaningful movements of human bodies, and is of
utmost importance in intelligent human-computer/robot interactions. In this paper, we …

Gesture recognition aims at understanding the ongoing human gestures. In this paper, we
present a deep architecture to learn spatiotemporal features for gesture recognition. The …

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 …

This paper reviews and discusses research advances on “explainable machine learning” in
computer vision. We focus on a particular area of the “Looking at People”(LAP) thematic …

The interest in action and gesture recognition has grown considerably in the last years. In
this paper, we present a survey on current deep learning methodologies for action and …

This paper proposes three simple, compact yet effective representations of depth
sequences, referred to respectively as dynamic depth images (DDI), dynamic depth normal …

Convolutional long short-term memory (LSTM) networks have been widely used for
action/gesture recognition, and different attention mechanisms have also been embedded …

Gestures are a common form of human communication and important for human computer
interfaces (HCI). Recent approaches to gesture recognition use deep learning methods …

Scene flow describes the motion of 3D objects in real world and potentially could be the
basis of a good feature for 3D action recognition. However, its use for action recognition …