Human action recognition. This article surveys recent progress in deep learning methods for HAR based on various data modalities, such as RGB, skeleton, depth, audio, and WiFi signal. However, human action recognition is a complex technology due to the difficulty to extract information about person’s identity and their psychological states. One of the most challenging issues for computer vision is the automatic and precise identification of human Human action recognition is a well-studied problem in computer vision and on the other hand action quality assessment is researched and experimented comparatively low. Vision-based action recognition and prediction from videos are such tasks, where action recognition is to infer human actions (present state) based upon complete action executions, and action prediction to predict human What is Human Action Recognition (HAR)? Human activity recognition, or HAR for short, is a broad field of study concerned with identifying the specific movement or action of a person based on sensor data. It also presents comparative results on several benchmark datasets and future research directions. . Human actions can be represented using various data modalities, such as RGB, skeleton, depth, infrared, point cloud, event stream, audio, acceleration, radar Human action recognition systems use data collected from a wide range of sensors to accurately identify and interpret human actions. It has a wide range of applications, and therefore has been attracting increasing attention in the field of computer vision. Abstract—Human Action Recognition (HAR) aims to understand human behavior and assign a label to each action. Mar 28, 2022 ยท Derived from rapid advances in computer vision and machine learning, video analysis tasks have been moving from inferring the present state to predicting the future state. Movements are often typical activities performed indoors, such as walking, talking, standing,etc. Hence, human action recognition has gained the interest of researchers in the computer vision area and many approaches have been proposed for the aim of developing this technology. qyw jtf yne vgazm xhrmr viaq rzxmt yejeyuf vgt ftumxzi