• Laser & Optoelectronics Progress
  • Vol. 55, Issue 6, 061010 (2018)
Tingting Gu1、1; , Haitao Zhao1、1; , and Shaoyuan Sun2、2;
Author Affiliations
  • 1 School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
  • 2 School of Information Science and Technology, Donghua University, Shanghai 201620, China
  • show less
    DOI: 10.3788/LOP55.061010 Cite this Article Set citation alerts
    Tingting Gu, Haitao Zhao, Shaoyuan Sun. Depth Estimation of Single Infrared Image Based on Interframe Information Extraction[J]. Laser & Optoelectronics Progress, 2018, 55(6): 061010 Copy Citation Text show less
    References

    [1] Lin D H, Fidler S, Urtasun R. Holistic scene understanding for 3D object detection with RGBD cameras. [C]∥Proceedings of IEEE International Conference on Computer Vision, 1417-1424(2013).

    [2] Saxena A, Chung S H, Ng A Y. 3-D depth reconstruction from a single still image[J]. International Journal of Computer Vision, 76, 53-69(2008). http://link.springer.com/article/10.1007/s11263-007-0071-y

    [3] Biswas J, Veloso M. Depth camera based indoor mobile robot localization and navigation. [C]∥Proceedings of IEEE International Conference on Robotics and Automation, 1697-1702(2012).

    [4] Torralba A, Oliva A. Depth estimation from imagestructure[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 1226-1238(2002). http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=1033214

    [5] Saxena A, Schulte J, Ng A Y. Depth estimation using monocular and stereo cues. [C]∥Proceedings of the 20 th International Joint Conference on Artifical Intelligence , 2197-2203(2007).

    [6] Liu B Y, Gould S, Koller D. Single image depth estimation from predicted semantic labels. [C]∥Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1253-1260(2010).

    [7] Russakovsky O, Deng J, Su H et al. ImageNet large scale visual recognition challenge[J]. International Journal of Computer Vision, 115, 211-252(2015). http://link.springer.com/article/10.1007/s11263-015-0816-y

    [8] Guo J. https://arxiv. org/pdf/1506.07224.pdf.(2015).

    [9] Dou Q, Chen H, Yu L Q et al. Multilevel contextual 3-D CNNs for false positive reduction in pulmonary nodule detection[J]. IEEE Transactions on Biomedical Engineering, 64, 1558-1567(2017). http://ieeexplore.ieee.org/document/7576695/

    [10] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017). http://dl.acm.org/citation.cfm?id=2999257

    [11] Simonyan K. https://arxiv. org/pdf/1409.1556.pdf.(2014).

    [12] Eigen D, Puhrsch C, Fergus R. Depth map prediction from a single image using a multi-scale deep network[J]. Proceedings of the 27 th International Conference on Neural Information Processing Systems , 2, 2366-2374(2014). http://www.oalib.com/paper/4082159

    [13] He K M, Zhang Z Y, Ren S Q et al. Deep residual learning for image recognition. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition(2016).

    [14] Laina I, Rupprecht C, Belagiannis V et al. Deeper depth prediction with fully convolutional residual networks. [C]∥Proceedings of 4 th International Conference on 3D Vision , 239-248(2016).

    [15] Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 79, 3431-3440(2015).

    [16] Li B, Dai Y C, Chen H H, soft-weight-sum inference[J]. Computer Science et al. https://arxiv. org/pdf/1705.00534.pdf.(2017).

    [17] Zhou T H, Brown M, Snavely N et al. Unsupervised learning of depth and ego-motion from video. [C]∥Proceedings of IEEE Conference on CComputer Vision and Pattern Recognition, 6612-6619(2017).

    [18] Garg R. Vijay K B G, Carneiro G, et al. Unsupervised CNN for single view depth estimation: geometry to the rescue. [C]∥Proceedings of European Conference on Computer Vision, 740-756(2016).

    [19] Godard C, mac Aodha O, Brostow G J. Unsupervised monocular depth estimation with left-right consistency. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 6602-6611(2017).

    [20] Kuznietsov Y, Stückler J, Leibe B. Semi-supervised deep learning for monocular depth mapprediction. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 6647-6655(2017).

    [21] Sun S Y, Li L N, Xi L. Depth estimation from monocular infrared images based on BP neural network model. [C]∥Proceedings of International Conference on Computer Vision in Remote Sensing, 237-241(2012).

    [22] Xu L, Zhao H T, Sun S Y. Monocular infrared image depth estimation based on deep convolutional neural networks[J]. Acta Optica Sinica, 36, 0715002(2016).

    [23] Wu S C, Zhao H T, Sun S Y. Depth estimation from monocular infrared video based on bi-recursive convolutional neural network[J]. Acta Optica Sinica, 37, 1215003(2017).

    [24] He J M, Qiu J, Liu C. Fusing feature point density and edge information for scene depth estimation[J]. Laser & Optoelectronics Progress, 54, 071101(2017).

    [25] Farnebäck G. Two-frame motion estimation based on polynomial expansion. [C]∥Proceedings of Scandinavian Conference on Image Analysis, 363-370(2003).

    [26] Ji S W, Xu W, Yang M et al. 3D convolutional neural networks for human action recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 221-231(2013). http://www.ncbi.nlm.nih.gov/pubmed/22392705/

    [27] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 770-778(2016).

    Tingting Gu, Haitao Zhao, Shaoyuan Sun. Depth Estimation of Single Infrared Image Based on Interframe Information Extraction[J]. Laser & Optoelectronics Progress, 2018, 55(6): 061010
    Download Citation