Results 301 to 310 of about 2,834,648 (359)

MMNet: A Model-Based Multimodal Network for Human Action Recognition in RGB-D Videos

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Human action recognition (HAR) in RGB-D videos has been widely investigated since the release of affordable depth sensors. Currently, unimodal approaches (e.g., skeleton-based and RGB video-based) have realized substantial improvements with increasingly ...
Bruce X. B. Yu, Y. Liu, Xiang Zhang, S. Zhong, Keith C. C. Chan   +4 more
semanticscholar   +1 more source

Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

European Conference on Computer Vision, 2016
3D action recognition – analysis of human actions based on 3D skeleton data – becomes popular recently due to its succinctness, robustness, and view-invariant representation. Recent attempts on this problem suggested to develop RNN-based learning methods
Jun Liu, Amir Shahroudy, Dong Xu, Gang Wang   +3 more
semanticscholar   +1 more source

Human action invarianceness for human action recognition

2015 9th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), 2015
The uniqueness of the human action shape or silhouete can be used for the human action recognition. Acquiring the features of human silhouette to obtained the concept of human action invarianceness have led to an important research in video surveillance domain. This paper discusses the investigation of this concept by extracting individual human action
Nilam Nur Amir Sjarif, Siti Mariyam Shamsuddin   +1 more
openaire   +1 more source

Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group

2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014
Recently introduced cost-effective depth sensors coupled with the real-time skeleton estimation algorithm of Shotton et al. [16] have generated a renewed interest in skeleton-based human action recognition.
Raviteja Vemulapalli, Felipe Arrate, R. Chellappa   +2 more
semanticscholar   +1 more source

A method for human action recognition

Image and Vision Computing, 2003
Abstract This article deals with the problem of classification of human activities from video. Our approach uses motion features that are computed very efficiently, and subsequently projected into a lower dimensional space where matching is performed.
Osama Masoud, Nikolaos Papanikolopoulos
openaire   +1 more source

On an algorithm for human action recognition

Expert Systems with Applications, 2019
Abstract Human action recognition which needs video processing in real time, requires large memory size and execution time. This work proposes a local maxima of difference image (LMDI) based interest point detection technique, random projection tree with overlapping split and modified voting score for human action recognition.
Suraj Prakash Sahoo, Samit Ari
openaire   +1 more source

View invariants for human action recognition

2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003
This paper presents two approaches for the representation and recognition of human action in video, aiming for view-point invariance. The paper first presents new results using a 2D approach presented earlier. Inherent limitations of the 2D approach are discussed and a new 3D approach that builds on recent work on 3D model-based invariants, is ...
Vasu Parameswaran, Rama Chellappa
openaire   +1 more source

Cross-Domain Human Action Recognition

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2012
Conventional human action recognition algorithms cannot work well when the amount of training videos is insufficient. We solve this problem by proposing a transfer topic model (TTM), which utilizes information extracted from videos in the auxiliary domain to assist recognition tasks in the target domain. The TTM is well characterized by two aspects: 1)
Wei Bian, Dacheng Tao, Yong Rui
openaire   +2 more sources

Multi-Stream Interaction Networks for Human Action Recognition

IEEE transactions on circuits and systems for video technology (Print), 2022
Skeleton-based human action recognition has received extensive attention due to its efficiency and robustness to complex backgrounds. Though the human skeleton can accurately capture the dynamics of human poses, it fails to recognize human actions ...
Haoran Wang, Baosheng Yu, Jiaqi Li, Linlin Zhang, Dongyue Chen   +4 more
semanticscholar   +1 more source

Feature covariance for human action recognition

2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA), 2016
In this paper, we present a novel method for human action recognition using covariance features. Computationally efficient action features are extracted from the skeleton of the subject performing the action. They aim to capture relative positions of the joints and motion over time.
Alexandre Perez, Hedi Tabia, David Declercq, Alain Zanotti   +3 more
openaire   +1 more source