IEEE Geoscience and Remote Sensing Magazine - September 2019 - 59

Computer Vision and Pattern Recognition Conf., 2017, pp. 5667-
5675. doi: 10.1109/CVPR.2017.700.
[106] S. Vijayanarasimhan, S. Ricco, C. Schmid, R. Sukthankar, and
K. Fragkiadaki, SfM-Net: Learning of structure and motion
from video. Computing Research Repository. 2017. [Online].
Available: https://arxiv.org/abs/1704.07804
[107] V. Rengarajan, A. N. Rajagopalan, and R. Aravind, "From bows
to arrows: Rolling shutter rectification of urban scenes," in Proc.
IEEE Computer Vision and Pattern Recognition Conf., Las Vegas,
NV, 2016, pp. 2773-2781.
[108] V. Rengarajan, Y. Balaji, and A. N. Rajagopalan, "Unrolling the
shutter: CNN to correct motion distortions," in Proc. IEEE Computer Vision and Pattern Recognition Conf., Honolulu, HI, 2017,
pp. 2345-2353.
[109] S. Im, H. Ha, G. Choe, H. Jeon, K. Joo, and I. S. Kweon, "High
quality structure from small motion for rolling shutter cameras," in Proc. Int. Conf. Computer Vision, Santiago, Chile, 2015, pp.
837-845.
[110] Y. Furukawa and H. Carlos, "Multi-view stereo: A tutorial,"
Found. Trends Comput. Graph. Vision, vol. 9, no. 1-2, pp. 1-148,
2015. doi: 10.1561/0600000052.
[111] S. Harwin and A. Lucieer, "Assessing the accuracy of georeferenced point clouds produced via multi-view stereopsis from unmanned aerial vehicle (UAV) imagery," Remote Sens., vol. 4, no.
6, pp. 1573-1599, 2012.
[112] J. Liu, B. Guo, W. Jiang, W. Gong, and X. Xiao, "Epipolar rectification with minimum perspective distortion for oblique
images," Sensors, vol. 16, no. 11, p. 1870, 2016. doi: 10.3390/
s16111870.
[113] J. Li, Y. Liu, S. Du, P. Wu, and Z. Xu, "Hierarchical and adaptive phase correlation for precise disparity estimation of UAV
images," IEEE Trans. Geosci. Remote Sens., vol. 54, no. 12, pp.
7092-7104, 2016.
[114] J. Zbontar and Y. LeCun, "Stereo matching by training a convolutional neural network to compare image patches," J. Mach.
Learning Res., vol. 17, no. 65, pp. 1-32, 2016.
[115] A. Seki and M. Pollefeys, "SGM-Nets: Semi-global matching
with neural networks," in Proc. IEEE Computer Vision and Pattern
Recognition Conf., 2017, pp. 6640-6649.
[116] A. Kendall, H. Martirosyan, S. Dasgupta, and P. Henr y,
"End-to-end learning of geometry and context for deep
stereo regression," in Proc. Int. Conf. Computer Vision, 2017,
pp. 66-75.
[117] M. Ji, J. Gall, H. Zheng, Y. Liu, and L. Fang, "SurfaceNet: An
end-to-end 3D neural network for multiview stereopsis," in
Proc. Int. Conf. Computer Vision, 2017, pp. 2326-2334.
[118] A. Kar, C. Häne, and J. Malik, "Learning a multi-view stereo machine," in Proc. Neural Information Processing Systems Conf., 2017,
pp. 364-375.
[119] P.-H. Huang, K. Matzen, J. Kopf, N. Ahuja, and J.-B. Huang,
"DeepMVS: Learning multi-view stereopsis," in Proc. IEEE Computer Vision and Pattern Recognition Conf., 2018, pp. 2821-2830.
[120] Y. Yao, Z. Luo, S. Li, T. Fang, and L. Quan, "MVSNet: Depth
inference for unstructured multi-view stereo," in Proc. European
Conf. Computer Vision, 2018, pp. 785-801. doi: 10.1007/978-3030-01237-3_47.
SEPTEMBER 2019

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

[121] J. Liu, S. Ji, C. Zhang, and Z. Qin, "Evaluation of deep learning based stereo matching methods: From ground to aerial
images," ISPRS Int. Archives Photogrammetry Remote Sens. Spatial
Inform. Sci., vol. 42, no. 2, pp. 593-597, 2018.
[122] S. Wu et al., "Specular-to-diffuse translation for multi-view reconstruction," in Proc. European Conf. Computer Vision, 2018, pp.
193-211.
[123] S. Kumar, Y. Dai, and H. Li, "Monocular dense 3D reconstruction of a complex dynamic scene from two perspective frames,"
in Proc. Int. Conf. Computer Vision, Venice, Italy, 2017, pp. 4649-
4657.
[124] X. Gao, L. Hu, H. Cui, S. Shen, and H. Zhanyi, "Accurate and efficient ground-to-aerial model alignment," Pattern Recogn., vol.
76, no. 4, pp. 288-302, 2018.
[125] T. Xiang, G.-S. Xia, and L. Zhang, "Image stitching with perspective-preserving warping," ISPRS Int. Archives Photogrammetry Remote Sens. Spatial Inform. Sci., vol. 3, no. 3, pp. 287-294,
2016.
[126] T.-Z. Xiang, G.-S. Xia, L. Zhang, and N. Huang, "Locally warping-based image stitching by imposing line constraints," in
Proc. Int. Conf. Pattern Recognition, Cancun, Mexico, 2016, pp.
4178-4183.
[127] X. Li, N. Hui, H. Shen, Y. Fu, and L. Zhang, "A robust mosaicking procedure for high spatial resolution remote sensing images," ISPRS J. Photogrammetry Remote Sens., vol. 109, pp. 108-125,
Nov. 2015.
[128] J. Tian, X. Li, F. Duan, J. Wang, and Y. Ou, "An efficient seam
elimination method for UAV images based on Wallis dodging
and Gaussian distance weight enhancement," Sensors, vol. 16,
no. 5, p. 662, 2016. doi: 10.3390/s16050662.
[129] M. Song, Z. Ji, S. Huang, and J. Fu, "Mosaicking UAV orthoimages using bounded Voronoi diagrams and watersheds," Int.
J. Remote Sens., vol. 39, no. 15-16, pp. 4960-4979, 2018. doi:
10.1080/01431161.2017.1350309.
[130] M. R. Faraji, X. Qi, and A. Jensen, "Computer vision-based
orthorectification and georeferencing of aerial image sets," J.
Appl. Remote Sens., vol. 10, no. 3, p. 036027, 2016. doi: 10.1117/1.
JRS.10.036027.
[131] G. Zhang, Y. He, W. Chen, J. Jia, and H. Bao, "Multi-viewpoint
panorama construction with wide-baseline images," IEEE
Trans. Image Process., vol. 25, no. 7, pp. 3099-3111, 2016.
[132] S. L. Andrea, A. G. Mark, M. S. Caitriana, and R. Albert, "Multispectral remote sensing from unmanned aircraft: Image
processing workflows and applications for rangeland environments," Remote Sens., vol. 3, no. 12, pp. 2529-2551, 2011.
[133] S. Bang, H. Kim, and H. Kim, "UAV-based automatic generation
of high-resolution panorama at a construction site with a focus
on preprocessing for image stitching," Automation Construction,
vol. 84, pp. 70-80, Dec. 2017.
[134] H. Yu, J. Wang, Y. Bai, W. Yang, and G.-S. Xia, "Analysis of
large-scale UAV images using a multi-scale hierarchical representation," Geo-spatial Inform. Sci., vol. 21, no. 1, pp. 33-44,
2018.
[135] M. Xia, J. Yao, R. Xie, L. Li, and W. Zhang, "Globally consistent
alignment for planar mosaicking via topology analysis," Pattern
Recogn., vol. 66, pp. 239-252, June 2017.

59
https://www.arxiv.org/abs/1704.07804
IEEE Geoscience and Remote Sensing Magazine - September 2019

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - September 2019
