A review of state-of-the-art techniques for abnormal human activity recognition
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 …
Rpan: An end-to-end recurrent pose-attention network for action recognition in videos
Recent studies demonstrate the effectiveness of Recurrent Neural Networks (RNNs) for
action recognition in videos. However, previous works mainly utilize video-level category as …
action recognition in videos. However, previous works mainly utilize video-level category as …
Perceiving the person and their interactions with the others for social robotics–a review
Social robots need to understand human activities, dynamics, and the intentions behind their
behaviors. Most of the time, this implies the modeling of the whole scene. The recognition of …
behaviors. Most of the time, this implies the modeling of the whole scene. The recognition of …
Learning convolutional action primitives for fine-grained action recognition
Fine-grained action recognition is important for many applications of human-robot
interaction, automated skill assessment, and surveillance. The goal is to segment and …
interaction, automated skill assessment, and surveillance. The goal is to segment and …
Learning asynchronous and sparse human-object interaction in videos
Human activities can be learned from video. With effective modeling it is possible to discover
not only the action labels but also the temporal structure of the activities, such as the …
not only the action labels but also the temporal structure of the activities, such as the …
Toyota smarthome untrimmed: Real-world untrimmed videos for activity detection
Designing activity detection systems that can be successfully deployed in daily-living
environments requires datasets that pose the challenges typical of real-world scenarios. In …
environments requires datasets that pose the challenges typical of real-world scenarios. In …
A hierarchical pose-based approach to complex action understanding using dictionaries of actionlets and motion poselets
In this paper, we introduce a new hierarchical model for human action recognition that is
able to categorize complex actions performed in videos. Our model is also able to perform …
able to categorize complex actions performed in videos. Our model is also able to perform …
[HTML][HTML] A self-organizing neural network architecture for learning human-object interactions
The visual recognition of transitive actions comprising human-object interactions is a key
component for artificial systems operating in natural environments. This challenging task …
component for artificial systems operating in natural environments. This challenging task …
[HTML][HTML] Unsupervised human activity analysis for intelligent mobile robots
The success of intelligent mobile robots operating and collaborating with humans in daily
living environments depends on their ability to generalise and learn human movements, and …
living environments depends on their ability to generalise and learn human movements, and …
Possibilistic activity recognition with uncertain observations to support medication adherence in an assisted ambient living setting
A recent trend in healthcare is to motivate patients to self-manage their health conditions in
home-based settings. Self-management programs guide and motivate patients to achieve …
home-based settings. Self-management programs guide and motivate patients to achieve …