Modeling kinect sensor noise for improved 3D reconstruction and tracking
Nguyen, C. V., Izadi, S., & Lovell, D. R. (2012) Modeling kinect sensor noise for improved 3D reconstruction and tracking. In Proceedings of the 2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), IEEE, Zurich, pp. 524-530.
We contribute an empirically derived noise model for the Kinect sensor. We systematically measure both lateral and axial noise distributions, as a function of both distance and angle of the Kinect to an observed surface. The derived noise model can be used to filter Kinect depth maps for a variety of applications. Our second contribution applies our derived noise model to the KinectFusion system to extend filtering, volumetric fusion, and pose estimation within the pipeline. Qualitative results show our method allows reconstruction of finer details and the ability to reconstruct smaller objects and thinner surfaces. Quantitative results also show our method improves pose estimation accuracy. © 2012 IEEE.
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|Item Type:||Conference Paper|
|Keywords:||3D reconstruction, Depth Map, Noise distribution, Noise models, Pose estimation, Quantitative result, Sensor noise, Imaging systems, Visualization, Sensors|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Deposited On:||07 Jan 2015 03:57|
|Last Modified:||19 Jan 2015 04:52|
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