Abstract
There are a lot of three-dimensional reconstruction applications of real scenes. The rise of low-cost sensors, like the Microsoft Kinect, suggests the development of systems cheaper than the existing ones. Nevertheless, data provided by this device are worse than that provided by more sophisticated sensors. In the academic and commercial world, some initiatives try to solve that problem. Studying that attempts, this work suggests the modification of super-resolution algorithm described by Mitzel et al. [1] in order to consider in its calculations colored images provided by Kinect. This change improved the super-resolved depth maps provided, mitigating interference caused by sudden changes of captured scenes. The tests showed the improvement of generated maps and analysed the impact of CPU and GPU algorithms implementation in the super-resolution step.
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References
Mitzel, D., Pock, T., Schoenemann, T., Cremers, D.: Video super resolution using duality based TV-L 1 optical flow. In: Denzler, J., Notni, G., Süße, H. (eds.) Pattern Recognition. LNCS, vol. 5748, pp. 432–441. Springer, Heidelberg (2009)
Leica Geosystems: (Leica Geosystems), http://www.leica-geosystems.com/en/index.htm
LFM: (LFM), http://www.lfm-software.com/lfm-products
Cardon, D.L., Fife, W.S., Archibald, J.K., Lee, D.J.: Fast 3D reconstruction for small autonomous robots. In: Proceedings of the 31st Annual Conference of IEEE Industrial Electronics Society (IECON 2005) (2005)
BodyMetrics (BodyMetrics), http://www.bodymetrics.com/
Chen, J., Bautembach, D., Izadi, S.: Scalable real-time volumetric surface reconstruction. ACM Trans. Graph. 32, 113:1–113:16 (2013)
Baran, I., Popović, J.: Automatic rigging and animation of 3D characters. ACM Transactions on Graphics 26, 72:1–72:8 (2007)
Cui, Y., Chang, W., Nöll, T., Stricker, D.: Kinectavatar: Fully automatic body capture using a single kinect. In: AACV, Workshop on Color Depth Fusion in Computer Vision (2012)
Tong, J., Zhou, J., Liu, L., Pan, Z., Yan, H.: Scanning 3D full human bodies using kinects. Technical report, Hohai University (2012)
Kazhdan, M., Bolitho, M., Hoppe, H.: Poisson surface reconstruction. In: Proceedings of the Fourth Eurographics Symposium on Geometry Processing, SGP 2006, pp. 61–70. Eurographics Association, Aire-la-Ville (2006)
Newcombe, R., Kim, D., Kohli, P.: Kinectfusion: Real-time dense surface mapping and tracking. In: ISMAR (2011)
Schuon, S., Theobalt, C., Davis, J., Thrun, S.: Lidarboost: Depth superresolution for tof 3D shape scanning. In: CPVR 2009 (2009)
Cui, Y., Schuon, S., Chan, D., Thrun, S., Theobalt, C.: 3D shape scanning with a time-offlight camera. In: IEEE Proc. CVPR (2010)
Chang, W., Zwicker, M.: Global registration of dynamic range scans for articulated model reconstruction. ACM Trans. Graph. 30 (2011)
OpenCV: (OpenCV), http://www.opencv.org
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dos Santos, L.T.A., Loaiza Fernandez, M.E., Raposo, A.B. (2014). Generating Super-Resolved Depth Maps Using Low-Cost Sensors and RGB Images. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8888. Springer, Cham. https://doi.org/10.1007/978-3-319-14364-4_61
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DOI: https://doi.org/10.1007/978-3-319-14364-4_61
Publisher Name: Springer, Cham
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