[2] Lin H C, Lü Q, Wei H, et al. Quadrotor autonomous flight and three-dimensional dense reconstruction based on VI-SLAM［J］. Acta Optica Sinica, 2018, 38(7): 0715004.
[3] Xiao J S, Tian H, Zou W T, et al. Stereo matching based on convolutional neural network［J］. Acta Optica Sinica, 2018, 38(8): 0815017.
[4] Gibson J J. The perception of the visual world［M］. Cambridge: The Riverside Press, 1950.
[5] Loianno G, Scaramuzza D, Kumar V. Special issue on high-speed vision-based autonomous navigation of UAVs［J］. Journal of Field Robotics, 2018, 35(1): 3-4.
[6] Meneses M C, Matos L N, Oprado B. Low-cost autonomous navigation system based on optical-flow classification［EB/OL］. (2018-03-11)［2018-10-15］. https:∥arxiv.org/abs/1803.03966.
[7] Wan F H. Research on multi-sensor based UAV obstacle avoidance technique［D］. Hangzhou: Zhejiang University of Technology, 2017.
[8] Dai B X. Research on obstacle avoidance method of MAV in indoor environment based on optical flow［D］. Chengdu: University of Electronic Science and Technology of China, 2015.
[9] Forster C, Zhang Z C, Gassner M, et al. SVO: Semidirect visual odometry for monocular and multicamera systems［J］. IEEE Transactions on Robotics, 2017, 33(2): 249-265.
[10] Engel J, Koltun V, Cremers D. Direct sparse odometry［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 40(3): 611-625.
[11] Longuet-Higgins H C, Prazdny K. The interpretation of a moving retinal image［J］. Proceedingsof the Royal Society of London B, 1980, 208(1173): 385-397.
[12] Matthies L, Szeliski R, Kanade T. Kalman filter-based algorithms for estimating depth from image sequences［M］. Heidelberg: Springer, 1993: 87-130.
[13] de Luca A, Oriolo G, Robuffo Giordano P. Feature depth observation for image-based visual servoing: theory and experiments［J］. The International Journal of Robotics Research, 2008, 27(10): 1093-1116.
[14] Sabatini S, Corno M, Fiorenti S, et al. Vision-based pole-like obstacle detection and localization for urban mobile robots［C］∥Proceedings of the 29th IEEE Intelligent Vehicles Symposium, June 26-30, 2018, Changshu, China.New York: IEEE, 2018: 1209-1214.
[15] Buczko M, Willert V. Flow-decoupled normalized reprojection error for visual odometry［C］∥Proceedings of IEEE 19th International Conference on Intelligent Transportation Systems, November 1-4, 2016, Rio de Janeiro, Brazil. New York: IEEE, 2016: 1161-1167.
[16] Jaegle A, Phillips S, Daniilidis K. Fast, robust, continuous monocular egomotion computation［C］∥Proceedings of IEEE International Conference on Robotics and Automation, May 16-21, 2016, Stockholm, Sweden. New York: IEEE, 2016: 773-780.
[17] Wu Z L, Li J, Guan Z Y, et al. Optical flow-based autonomous landing control for fixed-wing small UAV［J］. Systems Engineering and Electronics, 2016, 38(12): 2827-2834.
[18] Guo L, Liu M Y, Wang Y, et al. A motion estimation method for optical flow detection device of aircraft with two cameras: CN104880187A［P/OL］. (2015-09-02)［2018-10-15］. https:∥patentimages.storage.googleapis.com/79/9a/cf/6a6371ddd46e75/CN104880187A.pdf.
[19] Geiger A, Lenz P, Urtasun R. The KITTI vision benchmark suite［EB/OL］. (2018-09-15)［2018-10-07］. http:∥www.cvlibs.net/datasets/kitti/eval_odometry.php.
[20] Buczko M, Willert V. Monocular outlier detection for visual odometry［C］∥Proceedings of IEEE Intelligent Vehicles Symposium, June 11-14, 2017, Los Angeles, CA, USA. New York: IEEE, 2017: 1124-1131.
[21] Zhang Y J. A course of computer vision［M］. Beijing: Posts & Telecom Press, 2011.
[22] Jitendra M. Dynamic perspective［EB/OL］. (2015-05-02)［2018-10-07］. http:∥www-inst.eecs.berkeley.edu/~cs280/sp15/lectures/4.pdf.
[23] Geiger A, Lenz P, Urtasun R. Are we ready for autonomous driving The KITTI vision benchmark suite［C］∥Proceedings of, June 16-21, 2012, Providence, RI, USA. New York: IEEE, 2012: 3354-3361.
