3D Human Action Recognition: Through the eyes of researchers
Abstract Human Action Recognition (HAR) has remained one of the most challenging tasks
in computer vision. With the surge in data-driven methodologies, the depth modality has …
in computer vision. With the surge in data-driven methodologies, the depth modality has …
A survey on anomalous behavior detection for elderly care using dense-sensing networks
Facing the gradual ageing society, elderly people living independently are in need of
serious attention. In order to assist them to live in a safer environment, the increasing cost of …
serious attention. In order to assist them to live in a safer environment, the increasing cost of …
Human activity recognition using machine learning methods in a smart healthcare environment
The rapid developments in information and communication technologies and wireless
communication networks have led to the utilization of the smart sensors. In modern …
communication networks have led to the utilization of the smart sensors. In modern …
Sensor based human activity recognition using adaboost ensemble classifier
A Subasi, DH Dammas, RD Alghamdi… - Procedia computer …, 2018 - Elsevier
Providing accurate information about human activity is an important task in a smart city
environment. Human activity is complex, and it is important to use the best technology and …
environment. Human activity is complex, and it is important to use the best technology and …
Iss2Image: A novel signal-encoding technique for CNN-based human activity recognition
T Hur, J Bang, T Huynh-The, J Lee, JI Kim, S Lee - Sensors, 2018 - mdpi.com
The most significant barrier to success in human activity recognition is extracting and
selecting the right features. In traditional methods, the features are chosen by humans …
selecting the right features. In traditional methods, the features are chosen by humans …
LSTM-based real-time action detection and prediction in human motion streams
Motion capture data digitally represent human movements by sequences of 3D skeleton
configurations. Such spatio-temporal data, often recorded in the stream-based nature, need …
configurations. Such spatio-temporal data, often recorded in the stream-based nature, need …
Sleep stage classification based on multi-level feature learning and recurrent neural networks via wearable device
Background Automatic sleep stage classification is essential for long-term sleep monitoring.
Wearable devices show more advantages than polysomnography for home use. In this …
Wearable devices show more advantages than polysomnography for home use. In this …
Content-based management of human motion data: survey and challenges
Digitization of human motion using skeleton representations offers exciting possibilities for a
large number of applications but, at the same time, requires innovative techniques for their …
large number of applications but, at the same time, requires innovative techniques for their …
Multi-sensor fusion based on multiple classifier systems for human activity identification
Multimodal sensors in healthcare applications have been increasingly researched because
it facilitates automatic and comprehensive monitoring of human behaviors, high-intensity …
it facilitates automatic and comprehensive monitoring of human behaviors, high-intensity …
Human action recognition with deep learning and structural optimization using a hybrid heuristic algorithm
Human action recognition (HAR) is a popular subject for academic society and other
stakeholders. Nowadays it has a wide-spread use for lots of practical applications such as …
stakeholders. Nowadays it has a wide-spread use for lots of practical applications such as …