Sensor-based and vision-based human activity recognition: A comprehensive survey
Human activity recognition (HAR) technology that analyzes data acquired from various types
of sensing devices, including vision sensors and embedded sensors, has motivated the …
of sensing devices, including vision sensors and embedded sensors, has motivated the …
A survey of deep learning: Platforms, applications and emerging research trends
WG Hatcher, W Yu - IEEE access, 2018 - ieeexplore.ieee.org
Deep learning has exploded in the public consciousness, primarily as predictive and
analytical products suffuse our world, in the form of numerous human-centered smart-world …
analytical products suffuse our world, in the form of numerous human-centered smart-world …
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 …
A comprehensive survey on the biometric recognition systems based on physiological and behavioral modalities
Biometrics is the branch of science that deals with the identification and verification of an
individual based on the physiological and behavioral traits. These traits or identifiers are …
individual based on the physiological and behavioral traits. These traits or identifiers are …
Multi-modal fusion network with multi-scale multi-path and cross-modal interactions for RGB-D salient object detection
Paired RGB and depth images are becoming popular multi-modal data adopted in computer
vision tasks. Traditional methods based on Convolutional Neural Networks (CNNs) typically …
vision tasks. Traditional methods based on Convolutional Neural Networks (CNNs) typically …
Early, intermediate and late fusion strategies for robust deep learning-based multimodal action recognition
SY Boulahia, A Amamra, MR Madi, S Daikh - Machine Vision and …, 2021 - Springer
Multimodal action recognition techniques combine several image modalities (RGB, Depth,
Skeleton, and InfraRed) for a more robust recognition. According to the fusion level in the …
Skeleton, and InfraRed) for a more robust recognition. According to the fusion level in the …
Multi-stream CNN: Learning representations based on human-related regions for action recognition
The most successful video-based human action recognition methods rely on feature
representations extracted using Convolutional Neural Networks (CNNs). Inspired by the two …
representations extracted using Convolutional Neural Networks (CNNs). Inspired by the two …
Deep learning-based anomaly detection in video surveillance: A survey
Anomaly detection in video surveillance is a highly developed subject that is attracting
increased attention from the research community. There is great demand for intelligent …
increased attention from the research community. There is great demand for intelligent …
A review of state-of-the-art techniques for abnormal human activity recognition
C Dhiman, DK Vishwakarma - Engineering Applications of Artificial …, 2019 - Elsevier
The concept of intelligent visual identification of abnormal human activity has raised the
standards of surveillance systems, situation cognizance, homeland safety and smart …
standards of surveillance systems, situation cognizance, homeland safety and smart …
View-invariant deep architecture for human action recognition using two-stream motion and shape temporal dynamics
C Dhiman, DK Vishwakarma - IEEE Transactions on Image …, 2020 - ieeexplore.ieee.org
Human action Recognition for unknown views, is a challenging task. We propose a deep
view-invariant human action recognition framework, which is a novel integration of two …
view-invariant human action recognition framework, which is a novel integration of two …