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

Convolutional neural networks (CNNs) have demonstrated exceptional results in the
analysis of time-series data when used for Human Activity Recognition (HAR). The manual …

Human activity recognition (HAR) remains a challenging yet crucial problem to address in
computer vision. HAR is primarily intended to be used with other technologies, such as the …

The three-dimensional convolutional neural network (3D-CNN) and long short-term memory
(LSTM) have consistently outperformed many approaches in video-based facial expression …

Sensor-based human activity recognition (S-HAR) has become an important and high-
impact topic of research within human-centered computing. In the last decade, successful …

Human action recognition (HAR) has gained significant attention recently as it can be
adopted for a smart surveillance system in Multimedia. However, HAR is a challenging task …

Surveillance system is acquiring an ample interest in the field of computer vision. Existing
surveillance system usually relies on optical or wearable sensors for indoor and outdoor …

Convolutional long short-term memory (LSTM) networks have been widely used for
action/gesture recognition, and different attention mechanisms have also been embedded …

Following the growing availability of video surveillance cameras and the need for
techniques to automatically identify events in video footages, there is an increasing interest …

This research paper introduces a new approach for human activity recognition from UAV-
captured video sequences. The proposed approach involves two phases: an offline phase …