The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Microsoft Kinect Sensor and Its Effect
Abstract
Recent advances in 3D depth cameras such as Microsoft Kinect sensors (www.xbox.com/en-US/kinect) have created many opportunities for multimedia computing. The Kinect sensor lets the computer directly sense the third dimension (depth) of the players and the environment. It also understands when users talk, knows who they are when they walk up to it, and can interpret their movements and translate them into a format that developers can use to build new experiences. While the Kinect sensor incorporates several advanced sensing hardware, this article focuses on the vision aspect of the Kinect sensor and its impact beyond the gaming industry.
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Citations
Cites
A flexible new technique for camera calibration
Zhang, Z. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.888718 · Cited by 15,004
Self-citation
Research works printed but not linked: 9
- cai, 0, 3D Deformable Face Tracking with a Commodity Depth Camera, Proc 11th European Conf Computer Vision (ECCV), iii, 229
- 10.1109/CVPR.2011.5995316 · DOI · Paper page
- 10.1109/ICCVW.2011.6130383 · DOI
- ren, 0, Robust Hand Gesture Recognition Based on Finger-Earth Movers Distance with a Commodity Depth Camera, Proc 19th ACM Int'l Conf Multimedia (ACM MM), 1093
- 10.1109/ISMAR.2011.6092379 · DOI
- 10.1145/2072298.2072454 · DOI
- 10.1109/CVPRW.2010.5543273 · DOI · Paper page
- 10.1145/2037826.2037857 · DOI
- tashev, 2011, Recent Advances in Human-Machine Interfaces for Gaming and Entertainment, Int'l J Information Security, 3, 69
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
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
CAD2RL: Real Single-Image Flight Without a Single Real Image
Sadeghi, F., & Levine, S. (2017) · Robotics: Science and Systems XIII · doi:10.15607/rss.2017.xiii.034 · Cited by 618
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
Skeleton-based action recognition via spatial and temporal transformer networks
Plizzari, C., Cannici, M., & Matteucci, M. (2021) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2021.103219 · Cited by 409
Metadata
- Authors
- Zhang, Z.
- Venue
- IEEE Multimedia
- Published
- 2012-02
- Volume
- 19
- Issue
- 2
- Pages
- 4-10
- ISSN
- 1070-986X (ISSN-L)
- OpenAlex
- W2056898157
- Cited by
- 2,487
- References
- 1
- FWCI
- 233.24
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
