Calibration of depth measurement model for Kinect-type 3D vision sensors
Abstract
Accuracy of depth measurement with Microsoft Kinect and similar 3D vision sensors depends on variations in sensor production. Sensor reading may show significant systematic errors that can be compensated in software by using an adequate depth calibration model. This paper presents one such model and a procedure for identification of its parameters. An example calibration is given to illustrate the procedure and the attained improvements.
Keywords:
Microsoft Kinect sensor / 3D sensing / depth camera / RGB-D camera / camera calibrationSource:
21st International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2013, Poster Proceedings, 2013, 61-64Publisher:
- Plzen : University of West Bohemia, Plzen, Czech Republic
Funding / projects:
- Research and development of ambient-intelligent service robots with anthropomorphic characteristics (RS-35003)
- Design of Robot as Assistive Technology in Treatement of Children with Developmental Disorders (RS-44008)
Note:
- Preprint of the paper Karan, B. “Calibration of depth measurement model for Kinect ‐ type 3D vision sensors.” In the 21st International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2013, Poster Proceedings, 61‐64, 2013. Published version is available at http://otik.zcu.cz/bitstream/handle/11025/10626/Karan.pdf
Institution/Community
Институт техничких наука САНУ / Institute of Technical Sciences of SASATY - CONF AU - Karan, Branko PY - 2013 UR - https://dais.sanu.ac.rs/123456789/717 AB - Accuracy of depth measurement with Microsoft Kinect and similar 3D vision sensors depends on variations in sensor production. Sensor reading may show significant systematic errors that can be compensated in software by using an adequate depth calibration model. This paper presents one such model and a procedure for identification of its parameters. An example calibration is given to illustrate the procedure and the attained improvements. PB - Plzen : University of West Bohemia, Plzen, Czech Republic C3 - 21st International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2013, Poster Proceedings T1 - Calibration of depth measurement model for Kinect-type 3D vision sensors SP - 61 EP - 64 UR - https://hdl.handle.net/21.15107/rcub_dais_717 ER -
@conference{ author = "Karan, Branko", year = "2013", abstract = "Accuracy of depth measurement with Microsoft Kinect and similar 3D vision sensors depends on variations in sensor production. Sensor reading may show significant systematic errors that can be compensated in software by using an adequate depth calibration model. This paper presents one such model and a procedure for identification of its parameters. An example calibration is given to illustrate the procedure and the attained improvements.", publisher = "Plzen : University of West Bohemia, Plzen, Czech Republic", journal = "21st International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2013, Poster Proceedings", title = "Calibration of depth measurement model for Kinect-type 3D vision sensors", pages = "61-64", url = "https://hdl.handle.net/21.15107/rcub_dais_717" }
Karan, B.. (2013). Calibration of depth measurement model for Kinect-type 3D vision sensors. in 21st International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2013, Poster Proceedings Plzen : University of West Bohemia, Plzen, Czech Republic., 61-64. https://hdl.handle.net/21.15107/rcub_dais_717
Karan B. Calibration of depth measurement model for Kinect-type 3D vision sensors. in 21st International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2013, Poster Proceedings. 2013;:61-64. https://hdl.handle.net/21.15107/rcub_dais_717 .
Karan, Branko, "Calibration of depth measurement model for Kinect-type 3D vision sensors" in 21st International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2013, Poster Proceedings (2013):61-64, https://hdl.handle.net/21.15107/rcub_dais_717 .