Wide Field of View Kinect Undistortion for Social Navigation Implementation
In planning navigation schemes for social robots, distinguishing between humans and other obstacles is crucial for obtaining a safe and comfortable motion. A Kinect camera is capable of fulfilling such a task but unfortunately can only deliver a limited field of view (FOV). Recently a lens that is capable of improving the Kinect’s FOV has become commercially available from Nyko. However, this lens causes a distortion in the RGB-D data, including the depth values. To address this issue, we propose a two-staged undistortion strategy. Initially, pixel locations in both RGB and depth images are corrected using an inverse radial distortion model. Next, the depth data is post-filtered using 3D point cloud analysis to diminish the noise as a result of the undistorting process and remove the ground/ceiling information. Finally, the depth values are rectified using a neural network filter based on laser-assisted training. Experimental results demonstrate the feasibility of the proposed approach for fixing distorted RGB-D data.
KeywordsKinect Fish Eye Lens Undistortion Neural Network
Unable to display preview. Download preview PDF.
- 2.Engelhard, N., Endres, F., Hess, J., Sturm, J., Burgard, W.: Real-time 3D Visual SLAM with a Hand-Held RGB-D Camera. In: Proc. of the RGB-D Workshop on 3D Perception in Robotics at the European Robotics Forum (2011)Google Scholar
- 3.Tran, J.: Low-Cost 3D Scene Reconstruction for Response Robots in Real Time. In: Proc. of IEEE Intl. Symp. on Safety, Security, and Rescue Robotics, pp. 161–166 (2011)Google Scholar
- 4.Tomari, R., Kobayashi, Y., Kuno, Y.: Multi-view Head Detection and Tracking with Long Range Capability for Social Navigation Planning. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Wang, S., Kyungnam, K., Benes, B., Moreland, K., Borst, C., DiVerdi, S., Yi-Jen, C., Ming, J. (eds.) ISVC 2011, Part II. LNCS, vol. 6939, pp. 418–427. Springer, Heidelberg (2011)CrossRefGoogle Scholar
- 5.Brown, D.: Decentering Distortion of Lenses. Photogrammetric Eng. 7, 444–462 (1966)Google Scholar
- 7.Shah, S., Aggarwal, J.K.: Mobile Robot Navigation and Scene Modeling Using Stereo Fish-Eye Lens System. Machine Vision and Application, 159–173 (1996)Google Scholar
- 8.de Villers, J., Nicolls, F.: Application of Neural Networks to Inverse Lens Distortion Modeling. In: Proc. of 21st Annual Symposium of the Pattern Recognition Society of South Africa, vol. 1, pp. 63–68 (2010)Google Scholar
- 9.Ahmed, M., Hemayed, E., Farag, A.: Neurocalibration: A Neural Network that Can Tell Camera Calibration Parameters. IEEE Trans. PAMI 79, 384–390 (1999)Google Scholar