Human action recognition from RGB-D (Red, Green, Blue and Depth) data has attracted
increasing attention since the first work reported in 2010. Over this period, many benchmark …

This paper surveys the state of the art on multimodal gesture recognition and introduces the
JMLR special topic on gesture recognition 2011–2015. We began right at the start of the …

The recently developed depth imaging technologies have provided new directions for
human activity recognition (HAR) without attaching optical markers or any other motion …

In the last decades there has been a tremendous increase in demand for Assistive
Technologies (AT) useful to overcome functional limitations of individuals and to improve …

The aim of Active and Assisted Living is to develop tools to promote the ageing in place of
elderly people, and human activity recognition algorithms can help to monitor aged people …

Inspired by the success of deep learning methods, for human activity recognition based on
individual vision cues, this paper presents a ConvNets based approach for activity …

The scarcity of trained therapist, economic imbalance, and an increasing amount of elderly
people are the reasons for poor rehabilitation treatment and inadequate healthcare facilities …

Human activity recognition (HAR) is a highly prized application in the pattern recognition
and the computer vision fields. Up till now, deep neural networks have acquired big attention …

Activity recognition which aims to accurately distinguish human actions in complex
environments plays a key role in human-robot/computer interaction. However, long-lasting …

Abstract Analysis of human behavior through visual information has been one of the active
research areas in computer vision community during the last decade. Vision-based human …