Human activity recognition in RGB-D videos by dynamic images
- 30 March 2020
- journal article
- research article
- Published by Springer Nature in Multimedia Tools and Applications
- Vol. 79 (27-28) , 19787-19801
Abstract
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Funding Information
- Nvidia (0322218017192)
- Science and Engineering Research Board (SERB), Government of India (ECR/2016/00652)
This publication has 29 references indexed in Scilit:
- Action recognition from depth sequences using weighted fusion of 2D and 3D auto-correlation of gradients featuresMultimedia Tools and Applications, 2016
- A survey of depth and inertial sensor fusion for human action recognitionMultimedia Tools and Applications, 2015
- Action Recognition From Depth Maps Using Deep Convolutional Neural NetworksIEEE Transactions on Human-Machine Systems, 2015
- Bilinear heterogeneous information machine for RGB-D action recognition2015
- HON4D: Histogram of Oriented 4D Normals for Activity Recognition from Depth Sequences2013
- A decision forest based feature selection framework for action recognition from RGB-depth cameras2013
- A design-of-experiment based statistical technique for detection of key-framesMultimedia Tools and Applications, 2011
- People detection in RGB-D data2011
- Real-time body gesture recognition using depth cameraElectronics Letters, 2011
- A tutorial on support vector regressionStatistics and Computing, 2004