Action recognition with trajectory-pooled deep-convolutional descriptors
Visual features are of vital importance for human action understanding in videos. This paper
presents a new video representation, called trajectory-pooled deep-convolutional descriptor …
presents a new video representation, called trajectory-pooled deep-convolutional descriptor …
Human action recognition using fusion of multiview and deep features: an application to video surveillance
Abstract Human Action Recognition (HAR) has become one of the most active research area
in the domain of artificial intelligence, due to various applications such as video surveillance …
in the domain of artificial intelligence, due to various applications such as video surveillance …
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 …
Hand-crafted and deep convolutional neural network features fusion and selection strategy: An application to intelligent human action recognition
Human action recognition (HAR) has gained much attention in the last few years due to its
enormous applications including human activity monitoring, robotics, visual surveillance, to …
enormous applications including human activity monitoring, robotics, visual surveillance, to …
Sequential deep learning for human action recognition
We propose in this paper a fully automated deep model, which learns to classify human
actions without using any prior knowledge. The first step of our scheme, based on the …
actions without using any prior knowledge. The first step of our scheme, based on the …
Stochastic recognition of physical activity and healthcare using tri-axial inertial wearable sensors
Featured Application The proposed technique is an application of physical activity detection,
analyzing three challenging benchmark datasets. It can be applied in sports assistance …
analyzing three challenging benchmark datasets. It can be applied in sports assistance …
Violent flows: Real-time detection of violent crowd behavior
T Hassner, Y Itcher… - 2012 IEEE computer …, 2012 - ieeexplore.ieee.org
Although surveillance video cameras are now widely used, their effectiveness is
questionable. Here, we focus on the challenging task of monitoring crowded events for …
questionable. Here, we focus on the challenging task of monitoring crowded events for …
Sparse representation based fisher discrimination dictionary learning for image classification
The employed dictionary plays an important role in sparse representation or sparse coding
based image reconstruction and classification, while learning dictionaries from the training …
based image reconstruction and classification, while learning dictionaries from the training …
Tased-net: Temporally-aggregating spatial encoder-decoder network for video saliency detection
TASED-Net is a 3D fully-convolutional network architecture for video saliency detection. It
consists of two building blocks: first, the encoder network extracts low-resolution …
consists of two building blocks: first, the encoder network extracts low-resolution …
A database for fine grained activity detection of cooking activities
While activity recognition is a current focus of research the challenging problem of fine-
grained activity recognition is largely overlooked. We thus propose a novel database of 65 …
grained activity recognition is largely overlooked. We thus propose a novel database of 65 …