A review of human activity recognition methods
Recognizing human activities from video sequences or still images is a challenging task due
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …
Abnormal behavior recognition for intelligent video surveillance systems: A review
AB Mabrouk, E Zagrouba - Expert Systems with Applications, 2018 - Elsevier
With the increasing number of surveillance cameras in both indoor and outdoor locations,
there is a grown demand for an intelligent system that detects abnormal events. Although …
there is a grown demand for an intelligent system that detects abnormal events. Although …
Vision-based human activity recognition: a survey
Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …
human activities using acquired information from various types of sensors. Although several …
Monocular human pose estimation: A survey of deep learning-based methods
Vision-based monocular human pose estimation, as one of the most fundamental and
challenging problems in computer vision, aims to obtain posture of the human body from …
challenging problems in computer vision, aims to obtain posture of the human body from …
Ensemble deep learning for skeleton-based action recognition using temporal sliding lstm networks
This paper addresses the problems of feature representation of skeleton joints and the
modeling of temporal dynamics to recognize human actions. Traditional methods generally …
modeling of temporal dynamics to recognize human actions. Traditional methods generally …
Distribution-aligned diffusion for human mesh recovery
Recovering a 3D human mesh from a single RGB image is a challenging task due to depth
ambiguity and self-occlusion, resulting in a high degree of uncertainty. Meanwhile, diffusion …
ambiguity and self-occlusion, resulting in a high degree of uncertainty. Meanwhile, diffusion …
RGB-D-based human motion recognition with deep learning: A survey
Human motion recognition is one of the most important branches of human-centered
research activities. In recent years, motion recognition based on RGB-D data has attracted …
research activities. In recent years, motion recognition based on RGB-D data has attracted …
Spatiotemporal co-attention recurrent neural networks for human-skeleton motion prediction
Human motion prediction aims to generate future motions based on the observed human
motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling …
motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling …
Energy efficiency in wireless sensor networks: A top-down survey
T Rault, A Bouabdallah, Y Challal - Computer networks, 2014 - Elsevier
The design of sustainable wireless sensor networks (WSNs) is a very challenging issue. On
the one hand, energy-constrained sensors are expected to run autonomously for long …
the one hand, energy-constrained sensors are expected to run autonomously for long …