Abstract
Constructing a 3D map/perception model of an unknown indoor or outdoor environment using robotics is of compelling research nowadays because of the importance of the automatic monitoring system. Available IMU sensors and mobile robot kinematics allow 3D reconstruction to be finished in near real-time using a very low cost robotic platform. In this paper, we describe a framework for dense 3D reconstruction on an inexpensive robotic platform using a webcam and robot wheel odometry. Our experimental results show that our technique is efficient and robust to a variety of indoor and outdoor environment scenarios with different scale and size.
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References
Hartley, R., Zisserman, A.: Multiple view geometry in computer vision. Cambridge University Press. ISBN: 0-521-54051-8 (2003)
Newcombe, R.A., Lovegrove, S.J., Davison, A.J.: DTAM: Dense tracking and mapping in real-time, ICCV, pp. 2320–2327 (2011)
Pollefeys, M., Nister, D., Frahm, D.J.M., Akbarzadeh, A., Mordohai, P., Clipp, B., Engels, C., Gallup, D., Kim, S.J., Merrell, P., Salmi, C., Sinha, S., Talton, B., Wang, L., Yang, Q., Stewenius, H., Yang, R., Welch, G., Towles, H.: Detailed real-time urban 3D reconstruction from video. IJCV 78(2–3), 143–167 (2008)
Pradeep, V., Rhemann, C., Izadi, S., Zach, C., Bleyer, M., Bathiche, S.: MonoFusion: Real-time 3D reconstruction of small scenes with a single web camera. In: The 13th IEEE International Symposium on Mixed and Augmented Reality, pp. 83–88 (2013)
Pizzoli, M., Forster, C., Scaramuzza, D.: REMODE: probabilistic, monocular dense reconstruction in real time. In: IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, pp. 2609–2616 (2014)
Saha, A., Bhowmick, B., Sinha, A.: A system for near real-time 3D reconstruction from multi-view using 4G enabled mobile. In: IEEE International Conference on Mobile Services (MS), pp. 1–7, (2014)
Tanskanen, P., Kolev, K., Meier, L., Paulsen, F.C., Saurer, O., Pollefeys, M.: Live metric 3D reconstruction on mobile phones. In: ICCV, pp. 65–72 (2013)
Bhowmick, B., Mallik, A., Saha, A.: Mobiscan3D: A low cost framework for real time dense 3D reconstruction on mobile devices. In: IEEE 11th International Conference on Ubiquitous Intelligence and Computing, IEEE 11th International Conference on and Autonomic and Trusted Computing, and IEEE 14th International Conference on Scalable Computing and Communications and Its Associated Workshops (UTC-ATC-ScalCom), pp. 783–788 (2014)
Mallik, A., Bhowmick, B., Alam, S.: A multi-sensor information fusion approach for efficient 3D reconstruction in smart phone. In: International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV), pp 291–298 (2015)
Davison, A.: Real-time simultaneous localisation and mapping with a single camera. In: IEEE International Conference on Computer Vision, pp. 1403–1410 (2003)
Deshpande, P., Reddy, V.R., Saha, A., Vaiapury, K., Dewangan, K., Dasgupta, R.: A next generation mobile robot with multi-mode sense of 3D perception. In: International Conference on Advanced Robotics (ICAR) Istanbul, pp 382–387, (2015)
Firebird VI. http://www.nex-robotics.com/fire-bird-vi-robot-platform.html (2015). Access 20 Oct 2015
Martinez, A., Fernández, E.: Learning ROS for robotics programming. PACKT Publishing Ltd. (2013). ISBN: 978-1-78216-144-8
ROS usb Camera Package. http://wiki.ros.org/usb_cam (2015). Accessed 20 Oct 2015
Zhang, Z.: Flexible camera calibration by viewing a plane from unknown orientations. In: International Conference on Computer Vision (ICCV’99), pp 666–673, (1999)
Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)
ROS Robot Pose EKF Package. http://wiki.ros.org/robot_pose_ekf (2015). Accessed 20 Oct 2015
ROS Robot Localization Package. http://wiki.ros.org/robot_localization. Accessed 20 Oct 2015
Hirschmuller, H., Scharstein, D.: Evaluation of stereo matching costs on images with radiometric differences. IEEE Trans. Pattern Anal. Machine Intell. 31(9), 1582–1599 (2009)
Brox, T., Malik, J.: Large displacement optical flow: descriptor matching in variational motion estimation. IEEE Trans. Pattern Anal. Mach. Intell. 33(3), 500–513 (2011)
Sundaram, N., Brox, T., Keutzer, K.: Dense point trajectories by GPU-accelerated large displacement optical flow. In: European Conference on Computer Vision (ECCV), pp. 438–451, Crete, Greece, Springer, LNCS (2010)
Ummenhofer, B., Brox, T.: Dense 3D reconstruction with a hand-held camera. Springer, Berlin Heidelberg (2012)
Hartley, R.I., Sturm, P.: Triangulation. Comput. Vis. Image Underst. 68(2), 146–157 (1997)
Nützi, G., Weiss, S., Scaramuzza, D., Siegwart, R.: Fusion of IMU and vision for absolute scale estimation in monocular SLAM. J. Intell. Robot Syst 61(1–4), 287–299 (2011)
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Dewangan, K., Saha, A., Vaiapury, K., Dasgupta, R. (2016). 3D Environment Reconstruction Using Mobile Robot Platform and Monocular Vision. In: Choudhary, R., Mandal, J., Auluck, N., Nagarajaram, H. (eds) Advanced Computing and Communication Technologies. Advances in Intelligent Systems and Computing, vol 452. Springer, Singapore. https://doi.org/10.1007/978-981-10-1023-1_22
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DOI: https://doi.org/10.1007/978-981-10-1023-1_22
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