Title :
Modeling Kinect Sensor Noise for Improved 3D Reconstruction and Tracking
Author :
Nguyen, Chuong V. ; Izadi, Shahram ; Lovell, David
Author_Institution :
CSIRO, Canberra, ACT, Australia
Abstract :
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.
Keywords :
computer vision; image fusion; image reconstruction; object tracking; pose estimation; 3D reconstruction; 3D tracking; Kinect depth maps; Kinect sensor noise modeling; KinectFusion system; axial noise distributions; lateral noise distributions; pose estimation; volumetric fusion; Cameras; Image edge detection; Mathematical model; Noise; Noise measurement; Robot sensing systems; Solid modeling;
Conference_Titel :
3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2012 Second International Conference on
Conference_Location :
Zurich
Print_ISBN :
978-1-4673-4470-8
DOI :
10.1109/3DIMPVT.2012.84