A comprehensive review on handcrafted and learning-based action representation approaches for human activity recognition
Human activity recognition (HAR) is an important research area in the fields of human
perception and computer vision due to its wide range of applications. These applications …
perception and computer vision due to its wide range of applications. These applications …
A review on computer vision-based methods for human action recognition
Human action recognition targets recognising different actions from a sequence of
observations and different environmental conditions. A wide different applications is …
observations and different environmental conditions. A wide different applications is …
Lstm networks using smartphone data for sensor-based human activity recognition in smart homes
Human Activity Recognition (HAR) employing inertial motion data has gained considerable
momentum in recent years, both in research and industrial applications. From the abstract …
momentum in recent years, both in research and industrial applications. From the abstract …
Human action recognition using transfer learning with deep representations
Human action recognition is an imperative research area in the field of computer vision due
to its numerous applications. Recently, with the emergence and successful deployment of …
to its numerous applications. Recently, with the emergence and successful deployment of …
Cascading pose features with CNN-LSTM for multiview human action recognition
Human Action Recognition (HAR) is a branch of computer vision that deals with the
identification of human actions at various levels including low level, action level, and …
identification of human actions at various levels including low level, action level, and …
Multi-view human action recognition using skeleton based-FineKNN with extraneous frame scrap** technique
Human action recognition (HAR) is one of the most active research topics in the field of
computer vision. Even though this area is well-researched, HAR algorithms such as 3D …
computer vision. Even though this area is well-researched, HAR algorithms such as 3D …
AnomalyNet: a spatiotemporal motion-aware CNN approach for detecting anomalies in real-world autonomous surveillance
Anomaly detection has significant importance for the development of autonomous
monitoring systems. Real-world anomalous events are complicated due to diverse human …
monitoring systems. Real-world anomalous events are complicated due to diverse human …
Robust learning for real-world anomalies in surveillance videos
Anomaly detection has significant importance for develo** autonomous surveillance
systems. Real-world anomalous events are far more complex and harder to capture due to …
systems. Real-world anomalous events are far more complex and harder to capture due to …
Human action recognition using deep rule-based classifier
In recent years, numerous techniques have been proposed for human activity recognition
(HAR) from images and videos. These techniques can be divided into two major categories …
(HAR) from images and videos. These techniques can be divided into two major categories …