Action Recognition from Arbitrary Views Using Transferable Dictionary Learning

Jingtian Zhang, Hubert P. H. Shum, Jungong Han and Ling Shao
IEEE Transactions on Image Processing (TIP), 2018

Impact Factor: 11.041# Citation: 43## REF 2021 Submission

Action Recognition from Arbitrary Views Using Transferable Dictionary Learning
# Impact factors from the Journal Citation Reports 2021
## Citation counts from Google Scholar as of 2022

Abstract

Human action recognition is crucial to many practical applications, ranging from human-computer interaction to video surveillance. Most approaches either recognize the human action from a fixed view or require the knowledge of view angle, which is usually not available in practical applications. In this paper, we propose a novel end-to-end framework to jointly learn a view-invariance transfer dictionary and a view-invariant classifier. The result of the process is a dictionary that can project real-world 2D video into a view-invariant sparse representation, and a classifier to recognize actions with an arbitrary view. The main feature of our algorithm is the use of synthetic data to extract view-invariance between 3D and 2D videos during the pre-training phase. This guarantees the availability of training data, and removes the hassle of obtaining real-world videos in specific viewing angles. Additionally, for better describing the actions in 3D videos, we introduce a new feature set called the3D dense trajectories to effectively encode extracted trajectory information on 3D videos. Experimental results on the IXMAS, N-UCLA, i3DPost and UWA3DII data sets show improvements over existing algorithms.

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BibTeX

@article{zhang18arbitrary,
 author={Zhang, Jingtian and Shum, Hubert P. H. and Han, Jungong and Shao, Ling},
 journal={IEEE Transactions on Image Processing},
 title={Action Recognition from Arbitrary Views Using Transferable Dictionary Learning},
 year={2018},
 volume={27},
 number={10},
 pages={4709--4723},
 numpages={15},
 doi={10.1109/TIP.2018.2836323},
 issn={1057-7149},
 publisher={IEEE},
}

RIS

TY  - JOUR
AU  - Zhang, Jingtian
AU  - Shum, Hubert P. H.
AU  - Han, Jungong
AU  - Shao, Ling
T2  - IEEE Transactions on Image Processing
TI  - Action Recognition from Arbitrary Views Using Transferable Dictionary Learning
PY  - 2018
VL  - 27
IS  - 10
SP  - 4709
EP  - 4723
DO  - 10.1109/TIP.2018.2836323
SN  - 1057-7149
PB  - IEEE
ER  - 

Plain Text

Jingtian Zhang, Hubert P. H. Shum, Jungong Han and Ling Shao, "Action Recognition from Arbitrary Views Using Transferable Dictionary Learning," IEEE Transactions on Image Processing, vol. 27, no. 10, pp. 4709-4723, IEEE, 2018.

Similar Research

Jingtian Zhang, Lining Zhang, Hubert P. H. Shum and Ling Shao, "Arbitrary View Action Recognition via Transfer Dictionary Learning on Synthetic Training Data", Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA), 2016
Zheming Zuo, Daniel Organisciak, Hubert P. H. Shum and Longzhi Yang, "Saliency-Informed Spatio-Temporal Vector of Locally Aggregated Descriptors and Fisher Vectors for Visual Action Recognition", Proceedings of the 2018 British Machine Vision Conference Workshop on Image Analysis for Human Facial and Activity Recognition (IAHFAR), 2018

 

 
 

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