Range map superresolution-inpainting, and reconstruction from sparse data

Y. Kil, B. Mederos, N. Amenta, Laser scanner super-resolution, in: Eurographics Symposium on Point-Based Graphics, 2006, pp. 9–16. U. Hahne, M. Alexa, Combining time-of-flight depth and stereo images without accurate extrinsic calibration, in: International Workshop on Dynamic 3D Imaging, 2007, pp. 1–8. H. Andreasson, R. Triebel, A. Lilienthal, Vision based interpolation of 3D laser scans, in: Proceedings of the International Conference on Autonomous Robots and Agents, 2006. Guomundsson, 2008, Fusion of stereo vision and Time-of-Flight imaging for improved 3D estimation, International Journal of Intelligent Systems Technologies and Applications, 5, 425, 10.1504/IJISTA.2008.021305 PMD Technologies, PMD [vision] S3 datasheet, 2009. <http://www.pmdtec.com/products-services/pmdvisionr-cameras/pmdvisionr-s3>. B. Huhle, S. Fleck, S, A. Schilling, Integrating 3D time-of-flight camera data and high resolution images for 3DTV applications, in: 3DTV-Conference, 2008, pp. 1–4. Irani, 1991, Improving resolution by image registration, Graphical Models and Image Processing, 53, 231, 10.1016/1049-9652(91)90045-L Geman, 1984, Stochastic relaxation, Gibbs distribution and the Bayesian restoration of images, IEEE Transactions on Pattern Analysis and Machine Intelligence, 6, 721, 10.1109/TPAMI.1984.4767596 Suresh, 2007, Robust and computationally efficient super-resolution algorithm, Journal of the Optical Society of America – A, 24, 984, 10.1364/JOSAA.24.000984 M. Levoy, The digital Michelangelo project, 2009. <http://graphics.stanford.edu/projects/mich>. Q. Yang, R. Yang, J. Davis, D. Nister, Spatial-depth super resolution for range images, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008, pp. 1–8. A.N. Rajagopalan, A. Bhavsar, F. Wallhoff, G. Rigoll, Resolution enhancement of pmd range maps, in: DAGM Symposium 2008, 2008, pp. 304–313. Sharp, 2007, Maximum likelihood registration of images with missing range data, IEEE Trans. Pattern Anal. Mach. Intell., 30, 120, 10.1109/TPAMI.2007.1130 J. Diebel, S. Thrun, An application of Markov random fields to range sensing, in: Conference on Neural Information Processing Systems (NIPS 2005), 2005. Scharstein, 2002, A taxonomy and evaluation of dense two-frame stereo correspondence algorithms, Int. J. Comput. Vision, 47, 7, 10.1023/A:1014573219977 C. Strecha, W. von Hansen, L. Van Gool, P. Fua, U. Thoennessen, On benchmarking camera calibration and multi-view stereo for high resolution imagery, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008, pp. 1–8. S. Seitz, B. Curless, J. Diebel, D. Scharstein, R. Szeliski, A comparison and evaluation of multi-view stereo reconstruction algorithms, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2006), vol. 1, 2006, pp. 519–528. Torres-Mendez, 2008, Inter-image statistics for 3d environment modeling, Int. J. Comput. Vision, 79, 137, 10.1007/s11263-007-0108-2 J. Davis, S.R. Marschner, M. Garr, M. Levoy, Filling holes in complex surfaces using volumetric diffusion, in: International Symposium on 3D Data Processing Visualization and Transmission, 2002, pp. 428–442. J. Verdera, V. Caselles, M. Bertalmio, G. Sapiro, Inpainting surface holes, in: IEEE International Conference on Image Processing (ICIP 2003), vol. 3, 2003, pp. 903–906. M. Bertalmo, G. Sapiro, V. Caselles, C. Ballester, Image inpainting, in: International Conference on Computer Graphics and Interactive Techniques, 2000, pp. 417–424. R. Sahay, A.N. Rajagopalan, Inpainting in shape from focus: taking a cue from motion parallax, in: British Machine Vision Conference (BMVC 2009), 2009. L. Wang, H. Jin, R. Yang, M. Gong, Stereoscopic inpainting: Joint color and depth completion from stereo images, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008, pp. 1–8. A. Bhavsar, A.N. Rajagopalan, Range map with missing data – joint resolution enhancement and inpainting, in: Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2008), 2008, pp. 359–365. P. Favaro, S. Osher, S. Soatto, L. Vese, 3D Shape from anisotropic diffusion, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2003), 2003, pp. 179–186. Subrahmanyam, 2010, A recursive framework for joint inpainting de-noising of photographic films, J. Opt. Soc. Am. A (JOSA A), 27, 1029 Boykov, 2001, Fast approximate energy minimizations via graph cuts, IEEE Trans. Pattern Anal. Mach. Vision, 23, 1222, 10.1109/34.969114 C. Rother, V. Kolmogorov, V. Lempitsky, M. Szummer, Optimizing binary MRFs via extended roof duality, in: Procedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007, pp. 1–8. P. Felzenszwalb, D. Huttenlocher, Efficient belief propagation for early vision, in: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 1996), vol. 1, 2004, pp. 261–268. Dorin, 1999, Mean shift: a robust approach toward feature space analysis, IEEE Trans Pattern Anal Mach Intell, 24, 603 T. Aydin, Y. Akgul, A new adaptive focus measure for shape from focus, in: British Machine Vision Conference (BMVC 2008), 2008. Li, 1995 K. Suresh, A.N. Rajagopalan, Robust space-variant super-resolution, in: IET International Conference on Visual Information Engineering (VIE 2006), 2006, pp. 600–605. Ohio State University, OSU (MSU/WSU) Range Image Database: 2007. <http://sampl.ece.ohiostate.edu/data/3DDB/RID/index.html>. Fischler, 1981, Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Commun ACM, 24, 381, 10.1145/358669.358692 D. Scharstein, R. Szeliski, High-accuracy stereo depth maps using structured light, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2003), vol. 1, 2003, pp. 195–202. D. Scharstein, C. Pal, Learning conditional random fields for stereo, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007, pp. 1–8. Schultz, 1994, A Bayesian approach to image expansion for improved definition, IEEE Trans Image Process, 3, 233, 10.1109/83.287017 University of Southern Florida, USF range image database: 1997. <http://marathon.csee.usf.edu/range/DataBase.html>. S. Schuon, C. Theobalt, J. Davis, S. Thrun, High-quality scanning using time-of-flight super-resolution, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008s, pp. 1–7. S. Schuon, C. Theobalt, J. Davis, S. Thrun, LidarBoost: Depth super-resolution for Tof 3D shape scanning, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009, pp. 343–350. A. Bhavsar, A.N. Rajagopalan, Inpainting large missing regions in range images, in: International Conference on Pattern Recognition (ICPR 2010), 2010, pp. 3464–3467. Mesa Imaging, SR4000 data sheet, 2010. <http://www.mesa-imaging.ch/prodview4k.php>. R. Pito, Characterization, calibration, and use of the perceptron laser range finder in a controlled environment, in: Technical Report MS-CIS-95-05, GRASP Lab, University of Pennsylvania, 1995. Y. Sun, J. Paik, J.R. Price, M.A. Abidi, Dense range image smoothing using adaptive regularization, in: International Conference on Image Processing, vol. 2, 2009, pp. 744–747. S. Bauer, B. Berkels, J. Hornegger, M. Rumpf, Joint ToF image denoising and registration with a CT surface in radiation therapy: International Conference on Scale Space Methods and Variational Methods in Computer Vision, 2011. X. Sun, P. Rosin, R.R. Martin, F. Langbein, Noise in 3D laser range scanner data, in: International Conference on Shape Modeling and Applications, 2008, pp. 37–45. V. Blanz, A. Mehl, T. Vetter, H.P. Seidel, A statistical method for robust 3D surface reconstruction from sparse data, in: International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT 2004), 2004, pp. 293–300. 2001 Zisserman, 2003 C. Robertson, R.B. Fisher, Empirical calibration method for adding colour to range images, in: International Symposium on 3D Processing, Visualization and Transmission (3DPVT 2002), 2002, pp. 558–561. K Umeda, G. Godin, M. Rioux, Registration of range and color images using gradient constraints and range intensity images, in: International Conference on Pattern Recognition, vol. 3, 2004, pp. 12–15. R. Kurazume, K. Nishino, Z. Zhang, K. Ikeuchi, Simultaneous 2D images and 3D geometric model registration for texture mapping utilizing reflectance attribute, in: Asian Conference on Computer Vision, 2002, pp. 99–106. A.J. Troccoli, New methods and tools for 3D-modeling of large scale outdoor scenes using range and color images, PhD Thesis, Columbia University, 2007. Hoover, 1996, An experimental comparison of range image segmentation algorithms, IEEE Trans. Pattern Anal. Mach. Intell., 18, 673, 10.1109/34.506791 I. Stamos, M. Leordeanu, Efficient model creation of large structures based on range segmentation, in: International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT 2004), 2004, pp. 447–454. Salvi, 2007, A review of recent range image registration methods with accuracy evaluation, Image Vision Comput., 25, 578, 10.1016/j.imavis.2006.05.012 M. Germann, M.D. Breitenstein, I. Park, H. Pfister, Automatic pose estimation for range images on the GPU, in: Technical Report TR2007-061, MERL, 2007. R. Srisinroongruang, Automated texture mapping of laser based range images, in: Master of Science Thesis, Texas Tech University, 2005. J. Park, H. Kim, Y. Tai, M. Brown, I. Kweon, High Quality Depth Map Upsampling for 3D-TOF Cameras, in: International Conference on Computer Vision (ICCV 2011), 2011.