In this paper, we present a method (Action-Fusion) for human action recognition from depth
maps and posture data using convolutional neural networks (CNNs). Two input descriptors …

The classification and recognition of human activities plays an important role in the fields of
security, crime prevention, medical surveillance, etc. The swings of the limbs during the …

Human machine interaction becomes one of the most research topics in multimedia
processing, traditional techniques for communication are developed in order to tackle …

Micro-Doppler signatures obtained from the Doppler radar are generally used for human
activity classification. However, if the angle between the direction of motion and radar …

This paper presents a new model of scale, rotation, and translations invariant interest point
descriptor for human actions recognition. The descriptor, HMIV (Hu Moment Invariants on …

In recent years, interest in real-time video sequences for human action recognition has risen
rapidly, and discrimination is required to identify which type of human action appears in the …

Human target is one of the main targets of radar detection. Many methods have been
proposed to improve the performance of human activities classification, including the neural …

Human action recognition from a video has received growing attention in computer vision
and has made significant progress in recent years. Action recognition is described as a …

Detection of motion is an essential and important step in many applications such as in the
use of video surveliance in security systems, anomaly detection, traffic monitoring, people …

Detection of motion of pixel is a significant step in several applications. This paper
emphasizes the research methodologies that use time as a parameter for detection of pixel …