The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Gesture recognition using Microsoft Kinect®
Abstract
Gesture recognition is essential for human - machine interaction. In this paper we propose a method to recognize human gestures using a Kinect®depth camera. The camera views the subject in the front plane and generates a depth image of the subject in the plane towards the camera. This depth image is then used for background removal, followed by generation of the depth profile of the subject. In addition to this, the difference between subsequent frames gives the motion profile of the subject and is used for recognition of gestures. These allow the efficient use of depth camera to successfully recognize multiple human gestures. The result of a case study involving 8 gestures is shown. The system was trained using a multi class Support Vector Machine.
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Citations
Cites
Picture Thresholding Using an Iterative Selection Method
(1978) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1978.4310039 · Cited by 2,262
Segmentation and recognition of continuous human activity
Ali, A., & Aggarwal, J. K. (2002) · doi:10.1109/event.2001.938863 · Cited by 158
Segmenting visual actions based on spatio-temporal motion patterns
Rui, Y., & Anandan, P. (2002) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2000.855807 · Cited by 105
Human Activity Recognition via 3-D joint angle features and Hidden Markov models
Uddin, M. Z., Thang, N. D., & Kim, T. (2010) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2010.5651953 · Cited by 27
Cited by
Analysis of the Accuracy and Robustness of the Leap Motion Controller
Weichert, F., Bachmann, D., Rudak, B., & Fisseler, D. (2013) · Sensors · doi:10.3390/s130506380 · Cited by 913
Survey on 3D Hand Gesture Recognition
Cheng, H., Yang, L., & Liu, Z. (2016) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2015.2469551 · Cited by 344
Qi, W., Ovur, S. E., Li, Z., Marzullo, A., & Song, R. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3089999 · Cited by 253
Metadata
- Authors
- Biswas, K. K., & Basu, S. K.
- Venue
- The 5th International Conference on Automation, Robotics and Applications
- Publisher
- IEEE
- Published
- 2011-12
- Pages
- 100-103
- OpenAlex
- W2072028093
- Cited by
- 273
- References
- 4
- FWCI
- 14.57
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Biswas, K. K., & Basu, S. K. (2011). Gesture recognition using Microsoft Kinect®. The 5th International Conference on Automation, Robotics and Applications. https://doi.org/10.1109/icara.2011.6144864
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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.
