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 …

Anomaly analysis is an important component of any surveillance system. In recent years, it
has drawn the attention of the computer vision and machine learning communities. In this …

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 …

Ongoing human action recognition is a challenging problem that has many applications,
such as video surveillance, patient monitoring, human–computer interaction, etc. This paper …

Online human gesture recognition has a wide range of applications in computer vision,
especially in human-computer interaction applications. Recent introduction of cost-effective …

Abstract Human Action Recognition (HAR) has achieved a remarkable milestone in the field
of computer vision. Apart from its varied applications in human–computer interactions …

This paper presents a novel and efficient framework for group activity analysis. People in a
scene can be intuitively represented by an undirected graph where vertices are people and …

This paper proposes a matrix-based feature selection and classification method that takes
the advantage of L 2, 1-norm regularization. Current studies show that feature extraction and …

Human action recognition is one of the most important topics in computer vision. Monitoring
elderly people and children, smart surveillance systems and human-computer interaction …

The aim of this paper is to present a novel integrated framework for the recognition of human
actions using a spatial distribution of edge gradient (SDEG) of human pose and detailed …