Extracting features from crowd flow analysis has become an important research challenge
due to its social cost and the impact of inadequate planning of high-quality services and …

Group activity recognition, which aims to simultaneously understand individual action and
group activity in video clips, plays a fundamental role in computer vision and video analysis …

Research on group activity recognition mostly leans on the standard two-stream approach
(RGB and Optical Flow) as their input features. Few have explored explicit pose information …

We introduce a novel deep learning-based group activity recognition approach called the
Pose Only Group Activity Recognition System (POGARS), designed to use only tracked …

There has been a tremendous advance in machine learning techniques especially for
automatic group activity recognition (GAR) over the past few decades. This review article …

Gesture is a natural form of human communication, and it is of great significance in human–
computer interaction. In the dynamic gesture recognition method based on deep learning …

Group activity recognition (GAR) is an increasingly popular topic in the field of computer
vision. Numerous researchers have proposed a range of methods to achieve outstanding …

To understand human behavior we must not just recognize individual actions but model
possibly complex group activity and interactions. Hierarchical models obtain the best results …

This work proposes a video understanding technique that primarily focuses on the individual
action recognition appearing in the video. The state-of-the-art showed promising work in …

In the realm of video understanding and analysis, solely relying on the appearance features
of individuals in video frames significantly falls short of enhancing the accuracy of group …