Abstract
The 3D reconstruction technology based on stereo vision directly acquires the 3D model of the object through two 2D images. The reconstruction is recovered highly automated. It does not require any prior information and special hardware support. However, for large outdoor scenes, the existing 3D reconstruction technology based on stereo vision often has detailed information loss and data scattering, which makes the reconstruction result less accurate. For this problem, a novel binocular vision system for 3D reconstruction in large-scale scene is proposed. This system uses the calibration rods to perform the calibration calculation based on the polar line correction, and then it utilizes the weighted least squares filter(WLSF) to denoise and smooth the depth map, finally, the point cloud is reconstructed. The results of experiment show that compared with the traditional stereo vision system, the calibration results of new system is more accurate and the calibration space is expanded. The depth map is smoother and less noisy. The system can reconstruct the 3D point cloud of large scene more stably and accurately, has high practical value.















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References
Burie JC, Bruyelle JL, Postaire JG (1995) Detecting and localising obstacles in front of a moving vehicle using linear stereo vision[J]. Math Comput Model 22(4):235–246
Farbman Z, Fattal R, Lischinski D, Szeliski R (2008) Edge-preserving decompositions for multi-scale tone and detail manipulation[J]. ACM Trans Graph 27(3):67–10
Gao S, Tong X, Chen P, Ye Z, Hu O, Wang B, Zhao C, Liu S, Xie H, Jin Y, Xu X, Liu S, Wei C (2019) Full-field deformation measurement by videogrammetry using self-adaptive window matching[J]. Photogramm Rec 34(165):36–62
Golodetz S, Cavallari T, Lord NA, Prisacariu VA, Murray DW, Torr PHS (2018) Collaborative large-scale dense 3D reconstruction with online inter-agent pose optimisation[J]. IEEE Trans Vis Comput Graph 24(11):2895–2905
Ha H, Han S, Lee J (2012) Fault detection on transmission lines using a microphone Array and an infrared thermal imaging camera[J]. IEEE Trans Instrum Meas 61(1):267–275
Hu Y (2011) Research on a three-dimensional reconstruction method based on the feature matching algorithm of a scale-invariant feature transform[J]. Math Comput Model 54(3):919–923
Hu Y, Chen Q, Feng S, Tao T, Asundi A, Zuo C (2019) A new microscopic telecentric stereo vision system - calibration, rectification, and three-dimensional reconstruction[J]. Opt Lasers Eng 113:14–22
Irijanti E, Nayan MY, Yusoff MZ (2011) Local stereo matching algorithm: using small-color census and sparse adaptive support weight[C]. In: National Postgraduate Conference IEEE
Liang X, Du Y, Wei D (2019) An Integrated Camera Parameters Calibration Approach for Robotic Monocular Vision Guidance[C]. In: 2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)
Maolin Q, Songde MA (2000) Overview of camera calibration for computer vision[J]. J Autom Sin 26(1):43–55
Park JH, Park HW (2006) A mesh-based disparity representation method for view interpolation and stereo image compression[J]. IEEE Trans Image Process 15(7):1751–1762
Schöps T, Sattler T, Häne C, Pollefeys M (2016) Large-scale outdoor 3D reconstruction on a mobile device[J]. Comput Vis Image Underst S1077314216301412:151–166
Shenyue W, Qiang L, Chaoran W et al (2017) Design of 3D reconstruction system for outdoor scene based on binocular stereo camera[J]. Comput Meas Control 25(11):137–140 145
Vlaminck M, Luong H, Goeman W, Philips W (2016) 3D scene reconstruction using omnidirectional vision and LiDAR: a hybrid approach[J]. Sensors 16(11):1923
Wu P, Liu Y, Ye M, Li J, du S (2017) Fast and adaptive 3D reconstruction with extensively high completeness[J]. IEEE Trans Multimedia 19(2):266–278
Yang L, Wang B, Zhang R et al (2017) Analysis on Location Accuracy for Binocular Stereo Vision System[J]. IEEE Photonics J (99):1
Yang F, Shuaiang R, Enqi L et al (2019) Calibration method and regulation algorithm of binocular distance measurement in the large scene of image monitoring for overhead transmission lines[J]. High Voltage Eng 45(2):377–385
Zhang Z (2000) A flexible new technique for camera calibration[J]. IEEE Trans Pattern Anal Mach Intell 22(11):1330–1334
Zhang C, Zhang Q (2018) Research on volumetric calculation of multi-vision geometry UAV image volume[C]. In: 2018 Fifth international workshop on earth observation and remote sensing applications (EORSA)
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This work was supported by National Natural Science Foundation of China under the grant number 61502297 and 51707113.
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Wang, D., Sun, H., Lu, W. et al. A novel binocular vision system for accurate 3-D reconstruction in large-scale scene based on improved calibration and stereo matching methods. Multimed Tools Appl 81, 26265–26281 (2022). https://doi.org/10.1007/s11042-022-12866-4
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DOI: https://doi.org/10.1007/s11042-022-12866-4