Full 3D Reconstruction From Multiple RGB-D Cameras

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[1]  Nanning Zheng,et al.  Point-to-line metric based Iterative Closest Point with bounded scale , 2009, 2009 4th IEEE Conference on Industrial Electronics and Applications.

[2]  George Wolberg,et al.  Multiview Geometry for Texture Mapping 2D Images Onto 3D Range Data , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[3]  Dieter Fox,et al.  Interactive 3D modeling of indoor environments with a consumer depth camera , 2011, UbiComp '11.

[4]  Richard Szeliski,et al.  A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[5]  Pavel Krsek,et al.  The Trimmed Iterative Closest Point algorithm , 2002, Object recognition supported by user interaction for service robots.

[6]  Tomás Pajdla,et al.  Consistent Multi-view Reconstruction from Epipolar Geometries with Outliers , 2003, SCIA.

[7]  Koichi Ito,et al.  Accurate and dense wide-baseline stereo matching using SW-POC , 2011, The First Asian Conference on Pattern Recognition.

[8]  Nanning Zheng,et al.  A Fast Multi-Resolution Iterative Closest Point Algorithm , 2010, 2010 Chinese Conference on Pattern Recognition (CCPR).

[9]  Olivier D. Faugeras,et al.  Multi-View Stereo Reconstruction and Scene Flow Estimation with a Global Image-Based Matching Score , 2007, International Journal of Computer Vision.

[10]  Marc Pollefeys,et al.  Robust multi-view camera calibration for wide-baseline camera networks , 2011, 2011 IEEE Workshop on Applications of Computer Vision (WACV).

[11]  Andrew J. Davison,et al.  Live dense reconstruction with a single moving camera , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[12]  Pascal Fua,et al.  On benchmarking camera calibration and multi-view stereo for high resolution imagery , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[13]  Ronald L. Graham,et al.  On the History of the Minimum Spanning Tree Problem , 1985, Annals of the History of Computing.

[14]  A. Murat Tekalp,et al.  Multi-View Image Registration for Wide-Baseline Visual Sensor Networks , 2006, 2006 International Conference on Image Processing.

[15]  Pavel Krsek,et al.  Robust Euclidean alignment of 3D point sets: the trimmed iterative closest point algorithm , 2005, Image Vis. Comput..

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

[17]  Andrew W. Fitzgibbon,et al.  Robust Registration of 2D and 3D Point Sets , 2003, BMVC.

[18]  Wolfgang Förstner,et al.  Robust Wide Baseline Scene Alignment Based on 3D Viewpoint Normalization , 2010, ISVC.

[19]  Stefan Gumhold,et al.  Feature Extraction From Point Clouds , 2001, IMR.

[20]  Michael A. Greenspan,et al.  The parallel iterative closest point algorithm , 2001, Proceedings Third International Conference on 3-D Digital Imaging and Modeling.

[21]  Nico Blodow,et al.  Fast Point Feature Histograms (FPFH) for 3D registration , 2009, 2009 IEEE International Conference on Robotics and Automation.

[22]  Christian Hoffmann,et al.  Continuous Stereo Self-Calibration by Camera Parameter Tracking , 2009, IEEE Transactions on Image Processing.

[23]  Andrew W. Fitzgibbon,et al.  KinectFusion: Real-time dense surface mapping and tracking , 2011, 2011 10th IEEE International Symposium on Mixed and Augmented Reality.

[24]  Michael Ying Yang,et al.  Robust alignment of wide baseline terrestrial laser scans via 3D viewpoint normalization , 2011, 2011 IEEE Workshop on Applications of Computer Vision (WACV).

[25]  Nico Blodow,et al.  Aligning point cloud views using persistent feature histograms , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[26]  Jana Kosecka,et al.  Adaptive RGB-D Localization , 2012, 2012 Ninth Conference on Computer and Robot Vision.