Laser & Optoelectronics Progress, Volume. 57, Issue 6, 061007(2020)

Unsupervised Monocular Depth Estimation by Fusing Dilated Convolutional Network and SLAM

Renyue Dai, Zhijun Fang*, and Yongbin Gao
Author Affiliations
  • School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201600, China
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    References(22)

    [1] Pan X L, You Y R, Wang Z Y et al. Virtual to real reinforcement learning for autonomous driving[C]∥Proceedings of the British Machine Vision Conference 2017, September 2017, London, UK., 11(2017).

    [3] Michalos G, Karagiannis P, Makris S et al. Augmented reality (AR) applications for supporting human-robot interactive cooperation[J]. Procedia CIRP, 41, 370-375(2016).

    [4] Zhou T H, Brown M, Snavely N et al. Unsupervised learning of depth and ego-motion from video. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 6612-6621(2017).

    [5] Eigen D, Puhrsch C, Fergus R. Depth map prediction from a single image using a multi-scale deep network. [C]∥Advances in Neural Information Processing Systems, December 8-13, 2014, Montreal, Quebec, Canada. Canada: NIPS, 2366-2374(2014).

    [6] Eigen D, Fergus R. Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 2650-2658(2015).

    [7] Liu F Y, Shen C H, Lin G S. Deep convolutional neural fields for depth estimation from a single image. [C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 5162-5170(2015).

    [8] Wang A J, Fang Z J, Gao Y B et al. Depth estimation of video sequences with perceptual losses[J]. IEEE Access, 6, 30536-30546(2018).

    [9] Tosi F, Aleotti F, Poggi M et al. Learning monocular depth estimation infusing traditional stereo knowledge. [C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition(CVPR), June 16-20, 2019, Long Beach, CA. New York: IEEE, 9799-9809(2019).

    [11] Garg R. Vijay K B G, Carneiro G, et al. Unsupervised CNN for single view depth estimation: geometry to the rescue[M]. ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9912, 740-756(2016).

    [12] Mayer N, Ilg E, Hausser P et al. A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 4040-4048(2016).

    [13] Zhan H Y, Garg R, Weerasekera C S et al. Unsupervised learning of monocular depth estimation and visual odometry with deep feature reconstruction. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 340-349(2018).

    [15] Zhou X Y, Zheng J Q. -01-26)[2019-07-03]. https:∥arxiv.gg363., site/abs/1901, 09203(2019).

    [16] Chen S, Wang L. An improved SIFT feature matching based on RANSAC algorithm[J]. Information Technology, 40, 39-43(2016).

    [17] Shi G J, Xu X Y, Dai Y P. SIFT feature point matching based on improved RANSAC algorithm. [C]∥2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, August 26-27, 2013, Hangzhou, China. New York: IEEE, 474-477(2013).

    [19] Kingma D P. -01-30)[2019-07-03]. https:∥arxiv., org/abs/1412, 6980(2017).

    [20] Luo C X, Yang Z H, Wang P et al. Every pixel counts ++: joint learning of geometry and motion with 3D holistic understanding[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(2019).

    [21] Li R H, Wang S, Long Z Q et al. UnDeepVO: monocular visual odometry through unsupervised deep learning. [C]∥2018 IEEE International Conference on Robotics and Automation (ICRA), May 21-25, 2018, Brisbane, QLD, Australia. New York: IEEE, 7286-7291(2018).

    [22] Kumar A R S, Bhandarkar S M, Prasad M. Monocular depth prediction using generative adversarial networks. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June 18-22, 2018, Salt Lake City, UT, USA. New York: IEEE, 413-421(2018).

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    Renyue Dai, Zhijun Fang, Yongbin Gao. Unsupervised Monocular Depth Estimation by Fusing Dilated Convolutional Network and SLAM[J]. Laser & Optoelectronics Progress, 2020, 57(6): 061007

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    Paper Information

    Category: Image Processing

    Received: Jul. 4, 2019

    Accepted: Aug. 28, 2019

    Published Online: Mar. 6, 2020

    The Author Email: Zhijun Fang (zjfang@foxmail.com)

    DOI:10.3788/LOP57.061007

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