The success of deep learning has been a catalyst to solving increasingly complex machine-
learning problems, which often involve multiple data modalities. We review recent advances …

The concept of intelligent visual identification of abnormal human activity has raised the
standards of surveillance systems, situation cognizance, homeland safety and smart …

Facial attribute analysis from facial images has always been a challenging task. Its practical
use cases are very different. This paper mentioned how to build machine learning models …

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 …

Sign language recognition is a challenging problem where signs are identified by
simultaneous local and global articulations of multiple sources, ie hand shape and …

Automatic detection and classification of dynamic hand gestures in real-world systems
intended for human computer interaction is challenging as: 1) there is a large diversity in …

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 …

Gesture is a natural interface in human-computer interaction, especially interacting with
wearable devices, such as VR/AR helmet and glasses. However, in the gesture recognition …

Touchless hand gesture recognition systems are becoming important in automotive user
interfaces as they improve safety and comfort. Various computer vision algorithms have …