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

Action recognition is a major branch of computer vision research. As a widely used
technology, action recognition has been applied to human–computer interaction, intelligent …

Human action recognition is a process of labeling video frames with action labels. It is a
challenging research topic since the background of videos is usually chaotic, which will …

The goal of human action recognition is to identify and understand the actions of people in
videos and export corresponding tags. In addition to spatial correlation existing in 2D …

In this paper, we propose an efficient and straightforward approach, video you only look
once (VideoYOLO), to capture the overall temporal dynamics from an entire video in a single …

The present research on the multi-sensor information fusion technology of mobile robots
aims to better understand the outdoor scene and improve the robot's perception of the …

In this paper, we propose a 3D Convolutional Neural Network (3DCNN) based multi-stream
framework to recognize American Sign Language (ASL) manual signs (consisting of …

Image data contain spatial information only, thus making two-dimensional (2D)
Convolutional Neural Networks (CNN) ideal for solving image classification problems. On …

Human action recognition from digital videos is a hot topic in the field of computer vision. It
has a pretty assortment of applications in a myriad of fields such as video surveillance …

Deep Neural Networks (DNNs) are machine learning models with a myriad of uses, such as
enabling tools that support professional workers or facilitating new modes of human …