The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Vision-based action recognition of construction workers using dense trajectories
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Cites
Histograms of Oriented Gradients for Human Detection
Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584
Large-Scale Video Classification with Convolutional Neural Networks
Karpathy, A., Toderici, G., Shetty, S., Leung, T., Sukthankar, R., & Fei-Fei, L. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.223 · Cited by 6,354
Hmdb: a large video database for human motion recognition
Kuehne, H., Jhuang, H., Garrote, E., Poggio, T., & Serre, T. (2011) · 2011 International Conference on Computer Vision · doi:10.1109/iccv.2011.6126543 · Cited by 3,965
ActivityNet: A large-scale video benchmark for human activity understanding
Heilbron, F. C., Escorcia, V., Ghanem, B., & Niebles, J. C. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298698 · Cited by 2,578
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
Dense Trajectories and Motion Boundary Descriptors for Action Recognition
Wang, H., Kläser, A., Schmid, C., & Liu, C.-L. (2013) · International Journal of Computer Vision · doi:10.1007/s11263-012-0594-8 · Cited by 1,669
The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities
Kuehne, H., Arslan, A., & Serre, T. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.105 · Cited by 571
A survey of video datasets for human action and activity recognition
Chaquet, J. M., Carmona, E. J., & Fernández-Caballero, A. (2013) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2013.01.013 · Cited by 455
Combining embedded accelerometers with computer vision for recognizing food preparation activities
Stein, S., & McKenna, S. J. (2013) · Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing · doi:10.1145/2493432.2493482 · Cited by 448
Cited by
Computer vision techniques in construction: A critical review
Xu, S., Wang, J., Shou, W., Ngo, T., Sadick, A.-M., & Wang, X. (2021) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-020-09504-3 · Cited by 409
ANN-based automated scaffold builder activity recognition through wearable EMG and IMU sensors
Bangaru, S. S., Wang, C., Busam, S. A., & Aghazadeh, F. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103653 · Cited by 114
Metadata
- Authors
- Yang, J., Shi, Z., & Wu, Z.
- Venue
- Advanced Engineering Informatics
- Publisher
- Elsevier BV
- Published
- 2016-08
- Volume
- 30
- Issue
- 3
- Pages
- 327-336
- ISSN
- 1474-0346 (ISSN-L)
- OpenAlex
- W2381252496
- Cited by
- 166
- References
- 9
- FWCI
- 8.67
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yang, J., Shi, Z., & Wu, Z. (2016). Vision-based action recognition of construction workers using dense trajectories. Advanced Engineering Informatics. https://doi.org/10.1016/j.aei.2016.04.009
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
