Abstract
We present in this paper an easy to use Computer Vision based platform for real-time 3D mapping, and augmented reality in indoors environments and its innovative application in Assisted Living. The information is displayed to the user by projecting it into the environment by a wearable device with embedded pico-projector. The system does not need markers or complicated set-ups, using low cost off-the-shelf equipment. It is also robust to small changes of the environment, and can make use of surrounding objects to provide more stable camera tracking. Pilot tests in health care centres and residences demonstrated the efficacy of the initial prototype.
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References
Castle, R.O., Murray, D.W.: Object recognition and localization while tracking and mapping. In: 8th IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2009, pp. 179–180 (October 2009)
Engel, J., Sturm, J., Cremers, D.: Semi-dense visual odometry for a monocular camera. In: IEEE International Conference on Computer Vision (ICCV 2013), pp. 1449–1456 (December 2013)
Furukawa, Y., Ponce, J.: Accurate, dense, and robust multiview stereopsis. IEEE Trans. on Pattern Analysis and Machine Intelligence 32(8), 1362–1376 (2010)
Goesele, M., Snavely, N., Curless, B., Hoppe, H., Seitz, S.M.: Multi-view stereo for community photo collections. In: IEEE 11th International Conference on Computer Vision, ICCV 2007, pp. 1–8 (October 2007)
Grisetti, Stachniss, Grzonka, Burgard: A tree parameterization for efficiently computing maximum likelihood maps using gradient descent. In: Proc. of Robotics: Science and Systems (2007)
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. Journal of Robotics Research 31(5), 647–663 (2012)
Karlsson, N., di Bernardo, E., Ostrowski, J., Goncalves, L., Pirjanian, P., Munich, M.E.: The vSLAM algorithm for robust localization and mapping. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation, ICRA 2005, pp. 24–29 (April 2005)
Klein, G., Murray, D.: Parallel tracking and mapping for small AR workspaces. In: Proc. Sixth IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR 2007), Nara, Japan (November 2007)
Meilland, M., Barat, C., Comport, A.: 3D high dynamic range dense visual slam and its application to real-time object re-lighting. In: IEEE Int. Symposium on Mixed and Augmented Reality (ISMAR 2013), pp. 143–152 (October 2013)
Minetto, R., Leite, N.J., Stolfi, J.: Afftrack: Robust tracking of features in variable-zoom videos. In: 2009 16th IEEE International Conference on Image Processing (ICIP), pp. 4285–4288 (November 2009)
Mistry, P., Maes, P.: Sixthsense: A wearable gestural interface. In: ACM SIGGRAPH, pp. 11:1–11:1. ACM, New York (2009)
Newcombe, Izadi, Hillige, Molyneaux, Kim, Davison, Kohi, Shotton, Hodges, Fitzgibbon: Kinectfusion: Real-time dense surface mapping and tracking. In: IEEE Int. Symp. on Mixed and Augmented Reality (ISMAR), pp. 127–136 (October 2011)
Newcombe, Lovegrove, Davison: Dtam: Dense tracking and mapping in real-time. In: IEEE Int. Conf. on Computer Vision (ICCV), pp. 2320–2327 (2011)
Nister, D., Stewenius, H.: Scalable recognition with a vocabulary tree. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 2161–2168 (2006)
Engineering System Technologies, Ekahau Vision, Sonitor Technologies, and Ubisense (2014)
Whelan, Kaess, Fallon, Johannsson, Leonard, McDonald: Kintinuous: Spatially extended kinectfusion. Technical Report MIT-CSAIL-TR-2012-020
Wu, Agarwal, Curless, Seitz: Multicore bundle adjustment. In: IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 3057–3064 (2011)
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Saracchini, R.F.V., Ortega, C.C. (2014). An Easy to Use Mobile Augmented Reality Platform for Assisted Living Using Pico-projectors. In: Chmielewski, L.J., Kozera, R., Shin, BS., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2014. Lecture Notes in Computer Science, vol 8671. Springer, Cham. https://doi.org/10.1007/978-3-319-11331-9_66
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DOI: https://doi.org/10.1007/978-3-319-11331-9_66
Publisher Name: Springer, Cham
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