The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …

Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …

Gesture recognition using machine-learning methods is valuable in the development of
advanced cybernetics, robotics and healthcare systems, and typically relies on images or …

Increased life expectancy coupled with declining birth rates is leading to an aging
population structure. Aging-caused changes, such as physical or cognitive decline, could …

Human action recognition has a wide range of applications including biometrics,
surveillance, and human computer interaction. The use of multimodal sensors for human …

In recent years, there has been a proliferation of works on human action classification from
depth sequences. These works generally present methods and/or feature representations …

A number of review or survey articles have previously appeared on human action
recognition where either vision sensors or inertial sensors are used individually …

This paper reviews the research literature on human motion analysis using inertial sensors
with the aim to find out: which configuration of sensors have been used to measure human …

Gesturing is an instinctive way of communicating to present a specific meaning or intent.
Therefore, research into sign language interpretation using gestures has been explored …

This paper presents a fusion approach for improving human action recognition based on two
differing modality sensors consisting of a depth camera and an inertial body sensor …