Vision-based vanishing point detection of autonomous navigation of mobile robot for outdoor applications
Cherubini, F. Spindler, & F. Chaumette. 2012. A new tentacles-based technique for avoiding obstacles during visual navigation. in Proc. IEEE International Conference on Robotics and Automation (ICRA). DOI:10.1109/ICRA.2012.6224584
Yeh, H. G., Wang, R., and Ary, J. 2016. “Automatic Driving System by Recognizing Road Signs Using Digital Image Processing.” ProQuest Dissertations Publishing, 10196473, pp. 1-28. Doi: 10.17265/2328-2223/2018.02.007
Kondo, Yuki & Numada, Munetoshi & Koshimizu, Hiroyasu & Yoshida, Ichiro. (2018). A Study on Fast and Robust Vanishing Point Detection System Using Fast M-Estimation Method and Regional Division for In-vehicle Camera. J. of Electrical Engineering. 6. 10.17265/2328-2223/2018.02.007.
G. Yang, Y. Wang, J. Yang and Z. Lu, "Fast and Robust Vanishing Point Detection Using Contourlet Texture Detector for Unstructured Road," in IEEE Access, vol. 7, pp. 139358-139367, 2019, doi: 10.1109/ACCESS.2019.2944244.
Han, J., Yang, Z., Hu, G. et al. Accurate and Robust Vanishing Point Detection Method in Unstructured Road Scenes. J Intell Robot Syst 94, 143–158 (2019). https://doi.org/10.1007/s10846-018-0814-8.
Khac, C.N.; Choi, Y.; Park, J.H.; Jung, H.-Y. A Robust Road Vanishing Point Detection Adapted to the Real-world Driving Scenes. Sensors 2021, 21, 2133. https://doi.org/10.3390/s21062133.
Yu, Z.; Zhu, L. Roust Vanishing Point Detection Based on the Combination of Edge and Optical Flow. In Proceedings of the 4th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), Nagoya, Japan, 13–15 July 2019; pp. 184–188, Doi: 10.1109/ACIRS.2019.8936016.
Yang, W.; Fang, B.; Tang, Y.Y. Fast and Accurate Vanishing Point Detection and Its Application in Inverse Perspective Mapping of Structured Road. IEEE Trans. Syst. Man Cybern. Syst. 2018, 48, 755–766, Doi: 10.1109/TSMC.2016.2616490.
Yong, Li & Ding, Weili & XuGuang, Zhang & Ju, Zhaojie. (2016). Road detection algorithm for Autonomous Navigation Systems based on dark channel prior and vanishing point in complex road scenes. Robotics and Autonomous Systems. 85. 10.1016/j.robot.2016.08.003.
Shichen Liu, Yichao Zhou, Yajie Zhao; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 12859-12868
C. Chang, J. Zhao and L. Itti, "DeepVP: Deep Learning for Vanishing Point Detection on 1 Million Street View Images," 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, pp. 4496-4503, doi: 10.1109/ICRA.2018.8460499.
H. Kong, J. Y. Audibert, & J. Ponce. August 2010. General road detection from a single image. IEEE Transactions on Image Processing, vol. 19, no. 8, pp. 2211–2220, https://doi.org/10.1109/TIP.2010.2045715
O. Miksik. May 2012. Rapid vanishing point estimation for general road detection. in Proc. IEEE International Conference on Robotics and Automation (ICRA), doi: 10.1109/ICRA.2012.6225206
C. Siagian, C. K. Chang, R. Voorhies, & L. Itti. March/April 2011. Beobot 2.0: Cluster architecture for mobile robotics, Journal of Field Robotics, vol. 28, no. 2, pp. 278–302, Doi: 10.1002/rob.20379
Siagian, Christian & Chang, Chin-Kai & Itti, Laurent. 2013. Mobile robot navigation system in outdoor pedestrian environment using vision-based road recognition. Proceedings - IEEE International Conference on Robotics and Automation. 564-571. 10.1109/ICRA.2013.6630630.
Tokuda, N., Funahashi, T., Numada, M., and Koshimizu, H. 2012. “The Line Detection by Hough Transform for Vanishing Point Detection.” Presented at ViEW2012, IS1-C6, Dec. 2012, Doi: 10.17265/2328-2223/2018.02.007
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