Abstract
In this paper we present a new RGB-D SLAM system specifically designed for mobile platforms. Though the basic approach has already been proposed, many relevant changes are required to suit a user-centered mobile environment. In particular, our implementation tackles the strict memory constraints and limited computational power of a typical tablet device, thus delivering interactive usability without hindering effectiveness. Real-time 3D reconstruction is achieved by projecting measurements from aligned RGB-D keyframes, so to provide the user with instant feedback. We analyze quantitatively the accuracy vs. speed trade-off of diverse variants of the proposed pipeline, we estimate the amount of memory required to run the application and we also provide qualitative results dealing with reconstructions of indoor environments.
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References
Borrmann, D., Elseberg, J., Lingemann, K., Nüchter, A., Hertzberg, J.: Globally consistent 3d mapping with scan matching. J. Robot. Auton. Syst. 56, 130–142 (2008)
Montemerlo, M., Thrun, S.: Large-scale robotic 3-d mapping of urban structures. In: International Symposium on Experimental Robotics (ISER), Singapore (2004)
Davison, A., Reid, I.D., Molton, N.D., Stasse, O.: MonoSLAM: real-time single camera SLAM. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 29, 1052–1067 (2007)
Klein, G., Murray, D.: Parallel tracking and mapping for small ar workspaces. In: International Symposium on Mixed and Augmented Reality (ISMAR), pp. 225–234 (2007)
Newcombe, R., Lovegrove, S., Davison, A.: DTAM: dense tracking and mapping in real-time. In: International Conference on Computer Vision (ICCV), pp. 2320–2327 (2011)
Occipital Inc.: The Structure sensor (2014). http://structure.io/
Creative Technology Ltd.: The Creative Senz3D sensor (2014). http://us.creative.com/p/web-cameras/creative-senz3d
Google Inc.: Project Tango (2014). https://www.google.com/atap/projecttango/
Kim, D., Davison, A., Kohli, P., Shotton, J., Hodges, S., Fitzgibbon, A.: KinectFusion: Real-time dense surface mapping and tracking. In: 10th IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pp. 127–136, Washington, DC, USA (2011)
Fioraio, N., Di Stefano, L.: SlamDunk: affordable real-time RGB-D SLAM. In: ECCV Workshop on Consumer Depth Cameras for Computer Vision, Zurich, Switzerland (2014)
Bylow, E., Sturm, J., Kerl, C., Kahl, F., Cremers, D.: Real-time camera tracking and 3d reconstruction using signed distance functions. In: Robotics: Science and Systems (RSS), Berlin, Germany (2013)
Whelan, T., Kaess, M., Leonard, J., Mcdonald, J.: Deformation-based loop closure for large scale dense RGB-D SLAM. In: International Conference on Intelligent Robot Systems (IROS), Tokyo, Japan (2013)
Henry, P., Krainin, M., Herbst, E., Ren, X., Fox, D.: RGB-D mapping: Using kinect-style depth cameras for dense 3D modeling of indoor environments. Int. J. Robot. Res. 31, 647–663 (2012)
Sturm, J., Engelhard, N., Endres, F., Burgard, W., Cremers, D.: A benchmark for the evaluation of RGB-D SLAM systems. In: International Conference on Intelligent Robot Systems (IROS) (2012)
Endres, F., Hess, J., Sturm, J., Cremers, D., Burgard, W.: 3D mapping with an RGB-D camera. IEEE Transactions on Robotics (2013)
Klein, G., Murray, D.: Parallel tracking and mapping on a camera phone. In: International Symposium on Mixed and Augmented Reality (ISMAR), pp. 83–86 Orlando, Florida, USA (2009)
Lee, W., Kim, K., Woo, W.: Mobile phone-based 3D modeling framework for instant interaction. In: International Conference on Computer Vision Workshops (ICCV Workshops) (2009)
Pan, Q., Arth, C., Rosten, E., Reitmayr, G., Drummond, T.: Rapid scene reconstruction on mobile phones from panoramic images. In: International Symposium on Mixed and Augmented Reality (ISMAR) (2011)
Tanskanen, P., Kolev, K., Meier, L., Camposeco, F., Saurer, O., Pollefeys, M.: Live metric 3D reconstruction on mobile phones. In: International Conference on Computer Vision (ICCV), Sydney, Australia (2013)
Bay, H., Ess, A., Tuytelaars, T., Gool, L.V.: Speeded-up robust features (SURF). Comput. Vis. Image Underst. 110, 346–359 (2008)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. (IJCV) 60, 91–119 (2004)
Muja, M., Lowe, D.G.: Fast approximate nearest neighbors with automatic algorithm configuration. In: International Conference on Computer Vision Theory and Applications (VISAPP) (2009)
Arun, K.S., Huang, T.S., Blostein, S.D.: Least-squares fitting of two 3-d point sets. IEEE Trans Pattern Anal. Mach. Intell. (PAMI) 9, 698–700 (1987)
Segal, M., Akeley, K.: The opengl graphics system: a specification (2004). http://www.opengl.org/documentation/specs/version2.0/glspec20.pdf
Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: ORB: an efficient alternative to SIFT or SURF. In: International Conference on Computer Vision (ICCV), Barcelona, Spain (2011)
Leutenegger, S., Chli, M., Siegwart, R.: BRISK: binary robust invariant scalable keypoints. In: International Conference on Computer Vision (ICCV) (2011)
Bradski, G.: The OpenCV library. Dr. Dobb’s J. Softw. Tools 25, 120–126 (2000)
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Brunetto, N., Fioraio, N., Di Stefano, L. (2015). Interactive RGB-D SLAM on Mobile Devices. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9010. Springer, Cham. https://doi.org/10.1007/978-3-319-16634-6_25
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DOI: https://doi.org/10.1007/978-3-319-16634-6_25
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