3D Reconstruction of Indoor Environment Using the Kinect Sensor

In recent years, there have been more and more research and applications on three-dimensional model reconstruction. With the help of Kinect, a somatosensory device invented by Microsoft, we realized three-dimensional model reconstruction process. Firstly, this paper introduced the acquisition mechanism of color and depth images. Because the color camera and the depth camera are not coincident, precise alignment of them is presented. Then, the depth image is filtered to remove small gaps using median filtering method. For bigger black portions, the interpolation algorithm is proposed. Finally, with the tridimensional triangularization algorithm, the three-dimensional scene is reconstructed with both color and depth information. The experimental results demonstrate that the proposed algorithm can produce high quality maps.

[1]  Shahram Izadi,et al.  Modeling Kinect Sensor Noise for Improved 3D Reconstruction and Tracking , 2012, 2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission.

[2]  Dieter Fox,et al.  RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments , 2010, ISER.

[3]  Wen-Yuan Chen,et al.  The non-contact human-height measurement scheme , 2011, 2011 International Conference on Machine Learning and Cybernetics.

[4]  Tomás Pajdla,et al.  3D with Kinect , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[5]  Toby Sharp,et al.  Real-time human pose recognition in parts from single depth images , 2011, CVPR.

[6]  Holly E. Rushmeier,et al.  The 3D Model Acquisition Pipeline , 2002, Comput. Graph. Forum.

[7]  Petros Daras,et al.  Real-Time, Full 3-D Reconstruction of Moving Foreground Objects From Multiple Consumer Depth Cameras , 2013, IEEE Transactions on Multimedia.

[8]  Rae-Hong Park,et al.  3-D reconstruction using the Kinect sensor and its application to a visualization system , 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[9]  Tan Jianrong An Algorithm for Topology Reconstruction from Unorganized Points Based on Local Flatness of Surface , 2002 .