The rapid and impromptu interest in the coupling of machine learning (ML) algorithms with
wearable and contactless sensors aimed at tackling real‐world problems warrants a …

Human activity recognition (HAR) aims to recognize activities from a series of observations
on the actions of subjects and the environmental conditions. The vision‐based HAR …

Research on depth-based human activity analysis achieved outstanding performance and
demonstrated the effectiveness of 3D representation for action recognition. The existing …

Achieving realistic, vivid, and human-like synthesized conversational gestures conditioned
on multi-modal data is still an unsolved problem due to the lack of available datasets …

Dynamics of human body skeletons convey significant information for human action
recognition. Conventional approaches for modeling skeletons usually rely on hand-crafted …

This paper presents a novel unsupervised domain adaptation method for cross-domain
visual recognition. We propose a unified framework that reduces the shift between domains …

Recently, skeleton based action recognition gains more popularity due to cost-effective
depth sensors coupled with real-time skeleton estimation algorithms. Traditional approaches …

Human motion recognition is one of the most important branches of human-centered
research activities. In recent years, motion recognition based on RGB-D data has attracted …

The rapid growth of the internet has reached the fourth generation, ie, web 4.0, which
supports Sentiment Analysis (SA) in many applications such as social media, marketing, risk …

Recently, Convolutional Neural Networks (ConvNets) have shown promising performances
in many computer vision tasks, especially image-based recognition. How to effectively use …