The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Human activity recognition from 3D data: A review
Abstract
Abstract Human activity recognition has been an important area of computer vision research since the 1980s. Various approaches have been proposed with a great portion of them addressing this issue via conventional cameras. The past decade has witnessed a rapid development of 3D data acquisition techniques. This paper summarizes the major techniques in human activity recognition from 3D data with a focus on techniques that use depth data. Broad categories of algorithms are identified based upon the use of different features. The pros and cons of the algorithms in each category are analyzed and the possible direction of future research is indicated.
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Citations
Cites
A survey on vision-based human action recognition
Poppe, R. (2010) · Image and Vision Computing · doi:10.1016/j.imavis.2009.11.014 · Cited by 2,242
RGBD-HuDaAct: A color-depth video database for human daily activity recognition
Ni, B., Wang, G., & Moulin, P. (2011) · 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops) · doi:10.1109/iccvw.2011.6130379 · Cited by 304
Cited by
NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis
Shahroudy, A., Liu, J., Ng, T.-T., & Wang, G. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.115 · Cited by 3,148
Nweke, H. F., Teh, Y. W., Al-garadi, M. A., & Alo, U. R. (2018) · Expert Systems with Applications · doi:10.1016/j.eswa.2018.03.056 · Cited by 930
Zhang, P., Lan, C., Xing, J., Zeng, W., Xue, J., & Zheng, N. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.233 · Cited by 691
View Adaptive Neural Networks for High Performance Skeleton-Based Human Action Recognition
Zhang, P., Lan, C., Xing, J., Zeng, W., Xue, J., & Zheng, N. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2896631 · Cited by 523
A survey of depth and inertial sensor fusion for human action recognition
Chen, C., Jafari, R., & Kehtarnavaz, N. (2017) · Multimedia Tools and Applications · doi:10.1007/s11042-015-3177-1 · Cited by 356
Metadata
- Authors
- Aggarwal, J. K., & Xia, L.
- Venue
- Pattern Recognition Letters
- Publisher
- Elsevier BV
- Published
- 2014-10
- Volume
- 48
- Pages
- 70-80
- ISSN
- 0167-8655 (ISSN-L)
- OpenAlex
- W2056339039
- Cited by
- 576
- References
- 2
- FWCI
- 51.04
- Type
- journal article
- Language
- en
- Open access
- closed
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- Aggarwal, J. K., & Xia, L. (2014). Human activity recognition from 3D data: A review. Pattern Recognition Letters. https://doi.org/10.1016/j.patrec.2014.04.011
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
