Robust dynamic 3-D measurements with motion-compensated phase-shifting profilometry

Abstract Phase-shifting profilometry (PSP) is a widely used approach to high-accuracy three-dimensional shape measurements. However, when it comes to moving objects, phase errors induced by the movement often result in severe artifacts even though a high-speed camera is in use. From our observations, there are three kinds of motion artifacts: motion ripples, motion-induced phase unwrapping errors, and motion outliers. We present a novel motion-compensated PSP to remove the artifacts for dynamic measurements of rigid objects. The phase error of motion ripples is analyzed for the N-step phase-shifting algorithm and is compensated using the statistical nature of the fringes. The phase unwrapping errors are corrected exploiting adjacent reliable pixels, and the outliers are removed by comparing the original phase map with a smoothed phase map. Compared with the three-step PSP, our method can improve the accuracy by more than 95% for objects in motion.

[1]  Qian Kemao,et al.  Two-dimensional windowed Fourier transform for fringe pattern analysis: Principles, applications and implementations , 2007 .

[2]  David J. Fleet,et al.  Performance of optical flow techniques , 1994, International Journal of Computer Vision.

[3]  Qian Chen,et al.  High-speed three-dimensional profilometry for multiple objects with complex shapes. , 2012, Optics express.

[4]  Gastón A. Ayubi,et al.  Pulse-width modulation in defocused three-dimensional fringe projection. , 2010, Optics letters.

[5]  Joaquim Salvi,et al.  Pattern codification strategies in structured light systems , 2004, Pattern Recognit..

[6]  Pierre Graebling,et al.  Robust Structured Light Coding for 3D Reconstruction , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[7]  Qican Zhang,et al.  Dynamic 3-D shape measurement method: A review , 2010 .

[8]  Richard Szeliski,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.

[9]  Baoli Yao,et al.  Phase-shift extraction for generalized phase-shifting interferometry. , 2009, Optics letters.

[10]  Shijie Feng,et al.  High-speed three-dimensional shape measurement for dynamic scenes using bi-frequency tripolar pulse-width-modulation fringe projection , 2013 .

[11]  L Z Cai,et al.  Generalized phase-shifting interferometry with arbitrary unknown phase steps for diffraction objects. , 2004, Optics letters.

[12]  Shenghui Zhao,et al.  Accurate Dynamic 3D Sensing With Fourier-Assisted Phase Shifting , 2015, IEEE Journal of Selected Topics in Signal Processing.

[13]  Luc Van Gool,et al.  Fast 3D Scanning with Automatic Motion Compensation , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Li Zhang,et al.  Rapid shape acquisition using color structured light and multi-pass dynamic programming , 2002, Proceedings. First International Symposium on 3D Data Processing Visualization and Transmission.

[15]  Emmanuel P. Baltsavias,et al.  A comparison between photogrammetry and laser scanning , 1999 .

[16]  Qian Chen,et al.  Real-time 3-D shape measurement with composite phase-shifting fringes and multi-view system. , 2016, Optics express.

[17]  Sai Siva Gorthi,et al.  Fringe projection techniques: Whither we are? , 2010 .

[18]  Xiang Peng,et al.  A generalized temporal phase unwrapping algorithm for three-dimensional profilometry , 2008 .

[19]  Anand Asundi,et al.  Phase error analysis and compensation for nonsinusoidal waveforms in phase-shifting digital fringe projection profilometry. , 2009, Optics letters.

[20]  Jiangtao Xi,et al.  Improving the accuracy performance of phase-shifting profilometry for the measurement of objects in motion. , 2014, Optics letters.

[21]  Anand K. Asundi,et al.  Micro Fourier Transform Profilometry (μFTP): 3D shape measurement at 10, 000 frames per second , 2017, ArXiv.

[22]  Joseph Shamir,et al.  Range Imaging With Adaptive Color Structured Light , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  A. Tünnermann,et al.  High-speed three-dimensional shape measurement using GOBO projection , 2016 .

[24]  Zonghua Zhang,et al.  Time efficient color fringe projection system for 3D shape and color using optimum 3-frequency Selection. , 2006, Optics express.

[25]  Song Zhang,et al.  Flexible 3-D shape measurement using projector defocusing. , 2009, Optics letters.

[26]  Zonghua Zhang,et al.  Review of single-shot 3D shape measurement by phase calculation-based fringe projection techniques , 2012 .

[27]  Qican Zhang,et al.  3-D shape measurement based on complementary Gray-code light , 2012 .

[28]  Sebastian Thrun,et al.  Real time motion capture using a single time-of-flight camera , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[29]  Lei Huang,et al.  Temporal phase unwrapping algorithms for fringe projection profilometry: A comparative review , 2016 .

[30]  Song Zhang Recent progresses on real-time 3D shape measurement using digital fringe projection techniques , 2010 .

[31]  Shijie Feng,et al.  General solution for high dynamic range three-dimensional shape measurement using the fringe projection technique , 2014 .

[32]  Shojiro Sakata,et al.  Reconstruction Of Surfaces Of 3-D Objects By M-array Pattern Projection Method , 1988, [1988 Proceedings] Second International Conference on Computer Vision.