Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

Recognizing human activities from video sequences or still images is a challenging task due
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …

In this work, we address human activity and hand gesture recognition problems using 3D
data sequences obtained from full-body and hand skeletons, respectively. To this aim, we …

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 …

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 …

Human action recognition targets recognising different actions from a sequence of
observations and different environmental conditions. A wide different applications is …

Since the launch of the Microsoft Kinect, scores of RGBD datasets have been released.
These have propelled advances in areas from reconstruction to gesture recognition. In this …

Action recognition is a very widely explored research area in computer vision and related
fields. We propose Kinematics Posture Feature (KPF) extraction from 3D joint positions …

Human activity recognition has been actively studied in the last three decades. Compared to
human action performed by a single person, human interaction is more complex due to the …

Gait analysis has gained new impetus over the past few years. This is mostly due to the
launch of low cost depth cameras accompanied with real time pose estimation algorithms. In …