3D convolutional neural networks for human action recognition
We consider the automated recognition of human actions in surveillance videos. Most
current methods build classifiers based on complex handcrafted features computed from the …
current methods build classifiers based on complex handcrafted features computed from the …
Histogram of oriented gradient-based fusion of features for human action recognition in action video sequences
Human Action Recognition (HAR) is the classification of an action performed by a human.
The goal of this study was to recognize human actions in action video sequences. We …
The goal of this study was to recognize human actions in action video sequences. We …
Sofa 2.0: Balancing advanced features in a hierarchical component model
Component-based software engineering is a powerful paradigm for building large
applications. However, our experience with building application of components is that the …
applications. However, our experience with building application of components is that the …
Action recognition using mined hierarchical compound features
A Gilbert, J Illingworth, R Bowden - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
The field of Action Recognition has seen a large increase in activity in recent years. Much of
the progress has been through incorporating ideas from single-frame object recognition and …
the progress has been through incorporating ideas from single-frame object recognition and …
An implementation of optimized framework for action classification using multilayers neural network on selected fused features
In video sequences, human action recognition is a challenging problem due to motion
variation, in frame person difference, and setting of video recording in the field of computer …
variation, in frame person difference, and setting of video recording in the field of computer …
Selective spatio-temporal interest points
B Chakraborty, MB Holte, TB Moeslund… - Computer Vision and …, 2012 - Elsevier
Recent progress in the field of human action recognition points towards the use of Spatio-
Temporal Interest Points (STIPs) for local descriptor-based recognition strategies. In this …
Temporal Interest Points (STIPs) for local descriptor-based recognition strategies. In this …
Video-based human action recognition using deep learning: a review
Human action recognition is an important application domain in computer vision. Its primary
aim is to accurately describe human actions and their interactions from a previously unseen …
aim is to accurately describe human actions and their interactions from a previously unseen …
Learning discriminative key poses for action recognition
In this paper, we present a new approach for human action recognition based on key-pose
selection and representation. Poses in video frames are described by the proposed …
selection and representation. Poses in video frames are described by the proposed …
Fast action detection via discriminative random forest voting and top-k subvolume search
Multiclass action detection in complex scenes is a challenging problem because of cluttered
backgrounds and the large intra-class variations in each type of actions. To achieve efficient …
backgrounds and the large intra-class variations in each type of actions. To achieve efficient …
Mining discriminative co-occurrence patterns for visual recognition
The co-occurrence pattern, a combination of binary or local features, is more discriminative
than individual features and has shown its advantages in object, scene, and action …
than individual features and has shown its advantages in object, scene, and action …