A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions
Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …
the computer vision. It has critical application in wide variety of tasks including gaming …
A review of convolutional-neural-network-based action recognition
G Yao, T Lei, J Zhong - Pattern Recognition Letters, 2019 - Elsevier
Video action recognition is widely applied in video indexing, intelligent surveillance,
multimedia understanding, and other fields. Recently, it was greatly improved by …
multimedia understanding, and other fields. Recently, it was greatly improved by …
Learning spatio-temporal representation with pseudo-3d residual networks
Abstract Convolutional Neural Networks (CNN) have been regarded as a powerful class of
models for image recognition problems. Nevertheless, it is not trivial when utilizing a CNN …
models for image recognition problems. Nevertheless, it is not trivial when utilizing a CNN …
Spatio-temporal lstm with trust gates for 3d human action recognition
Abstract 3D action recognition–analysis of human actions based on 3D skeleton data–
becomes popular recently due to its succinctness, robustness, and view-invariant …
becomes popular recently due to its succinctness, robustness, and view-invariant …
Vidtr: Video transformer without convolutions
Abstract We introduce Video Transformer (VidTr) with separable-attention for video
classification. Comparing with commonly used 3D networks, VidTr is able to aggregate …
classification. Comparing with commonly used 3D networks, VidTr is able to aggregate …
A comprehensive study of deep video action recognition
Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …
last decade, we have witnessed great advancements in video action recognition thanks to …
Skeleton-based action recognition using spatio-temporal LSTM network with trust gates
Skeleton-based human action recognition has attracted a lot of research attention during the
past few years. Recent works attempted to utilize recurrent neural networks to model the …
past few years. Recent works attempted to utilize recurrent neural networks to model the …
A deep hybrid learning model to detect unsafe behavior: Integrating convolution neural networks and long short-term memory
Computer vision and pattern recognition approaches have been applied to determine
unsafe behaviors on construction sites. Such approaches have been reliant on the …
unsafe behaviors on construction sites. Such approaches have been reliant on the …
Mict: Mixed 3d/2d convolutional tube for human action recognition
Human actions in videos are three-dimensional (3D) signals. Recent attempts use 3D
convolutional neural networks (CNNs) to explore spatio-temporal information for human …
convolutional neural networks (CNNs) to explore spatio-temporal information for human …
Audio-visual emotion recognition in video clips
This paper presents a multimodal emotion recognition system, which is based on the
analysis of audio and visual cues. From the audio channel, Mel-Frequency Cepstral …
analysis of audio and visual cues. From the audio channel, Mel-Frequency Cepstral …