• Acta Optica Sinica
  • Vol. 40, Issue 5, 0520001 (2020)
Lin Fu1, Haibo Hong2, Xi Wang1, Gaobo Xiao1, and Mingjun Ren1、*
Author Affiliations
  • 1State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • 2Shanghai Spaceflight Precision Machinery Institute, Shanghai 200240, China
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    DOI: 10.3788/AOS202040.0520001 Cite this Article Set citation alerts
    Lin Fu, Haibo Hong, Xi Wang, Gaobo Xiao, Mingjun Ren. Non-Lambertian Photometric Stereo Vision Based on Inverse Reflectance Model[J]. Acta Optica Sinica, 2020, 40(5): 0520001 Copy Citation Text show less
    References

    [1] Xu K, Zhou P, Yang C L. On-line detection technique of tiny surface defects for metal plates and strips based on photometric stereo[J]. Journal of Mechanical Engineering, 49, 25-29(2013).

    [2] Liu R X, Li L Q, Wang J et al. The evaluation of fabric pleat grade based on photometric stereo[J]. Journal of Donghua University(Natural Science Edition), 39, 48-52, 59(2013).

    [3] Li J, Ma Y C, Zhang Y J et al. 3D digitization of non-rigid objects using improved color photometric stereo method[J]. Journal of Computer-Aided Design & Computer Graphics, 27, 1750-1758(2015).

    [4] Woodham R J. Photometric method for determining surface orientation from multiple images[J]. Optical Engineering, 19, 191139(1980).

    [5] Zhang J. Research on 3D model reconstruction algorithm based on photometric stereo image Xi'an:[D]. Northwestern Polytechnical University(2004).

    [6] Lin M Q. Research and implementation of 3D reconstruction technology based on photometric stereo method[D]. Shenyang: Northeastern University(2010).

    [7] Xu Q X. Research on 3D reconstruction of detailed features based on photometric stereo[D]. Wuhan: Huazhong University of Science and Technology(2011).

    [8] León F P. Lindner C, van Gorkom D. Surface segmentation by variable illumination[J]. CIRP Annals, 56, 549-552(2007).

    [9] Smith M, Smith G, Hill T. Gradient space analysis of surface defects using a photometric stereo derived bump map[J]. Image and Vision Computing, 17, 321-332(1999).

    [10] Kang D, Jang Y J, Won S. Development of an inspection system for planar steel surface using multispectral photometric stereo[J]. Optical Engineering, 52, 039701(2013).

    [11] Miyazaki D, Hara K, Ikeuchi K. Median photometric stereo as applied to the Segonko Tumulus and museum objects[J]. International Journal of Computer Vision, 86, 229-242(2010).

    [12] Ikehata S, Aizawa K. Photometric stereo using constrained bivariate regression for general isotropic surfaces. [C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 2187-2194(2014).

    [13] Matusik W, Pfister H, Brand M et al. A data-driven reflectance model. [C]∥ACM SIGGRAPH 2003 Papers on-SIGGRAPH'03, July 27-31, 2003, San Diego, California. New York: ACM, 759-769(2003).

    [14] Wu L, Ganesh A, Shi B X et al. Robust photometric stereo via low-rank matrix completion and recovery[M]. ∥Kimmel R, Klette R, Sugimoto A. Computer vision-ACCV 2010. Lecture notes in computer science. Berlin, Heidelberg: Springer, 6494, 703-717(2011).

    [15] Ikehata S, Wipf D, Matsushita Y et al. Robust photometric stereo using sparse regression. [C]∥2012 IEEE Conference on Computer Vision and Pattern Recognition, June 16-21, 2012, Providence, RI, USA. New York: IEEE, 318-325(2012).

    [16] Queau Y, Wu T, Lauze F et al. A non-convex variational approach to photometric stereo under inaccurate lighting. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 350-359(2017).

    [17] Hertzmann A, Seitz S M. Example-based photometric stereo: shape reconstruction with general, varying BRDFs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27, 1254-1264(2005).

    [18] Yang M, Fang Y H, Wu J et al. Multiple-component polarized bidirectional reflectance distribution function model for painted surfaces based on Kubelka-Munk theory[J]. Acta Optica Sinica, 38, 0126002(2018).

    [19] Goldman D B, Curless B, Hertzmann A et al. Shape and spatially-varying BRDFs from photometric stereo. [C]∥Tenth IEEE International Conference on Computer Vision (ICCV'05), October 17-21, 2005, Beijing, China. New York: IEEE, 1, 8814797(2005).

    [20] Ward G J. Measuring and modeling anisotropic reflection[J]. ACM SIGGRAPH Computer Graphics, 26, 265-272(1992).

    [21] Alldrin N, Zickler T, Kriegman D. Photometric stereo with non-parametric and spatially-varying reflectance. [C]∥2008 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2008, Anchorage, AK, USA. New York: IEEE, 10139961(2008).

    [22] Shi B X, Tan P, Matsushita Y et al. Bi-polynomial modeling of low-frequency reflectances[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36, 1078-1091(2014).

    [23] Chandraker M, Ramamoorthi R. What an image reveals about material reflectance. [C]∥2011 International Conference on Computer Vision, November 6-13, 2011, Barcelona, Spain. New York: IEEE, 1076-1083(2011).

    [24] Shen H L, Han T Q, Li C G. Efficient photometric stereo using kernel regression[J]. IEEE Transactions on Image Processing, 26, 439-451(2017).

    [25] Santo H, Samejima M, Sugano Y et al. Deep photometric stereo network. [C]∥2017 IEEE International Conference on Computer Vision Workshops (ICCVW), October 22-29, 2017, Venice, Italy. New York: IEEE, 501-509(2017).

    [26] Silver W M. Determining shape and reflectance using multiple images[D]. USA: Massachusetts Institute of Technology(1980).

    [27] Hui Z, Sankaranarayanan A C. Shape and spatially-varying reflectance estimation from virtual exemplars[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 2060-2073(2017).

    [28] Hui Z, Sunkavalli K, Lee J Y et al. Reflectance capture using univariate sampling of BRDFs. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 5372-5380(2017).

    [29] Nie Y. Photometric stereo with near-field quasi point light sources[D]. Shenzhen: University of Chinese Academy of Sciences, 21-30(2016).

    [30] Wang X, Zhang Y S, Xu C et al. Bidirectional reflectance distribution function modeling approach of space objects' fold material[J]. Acta Optica Sinica, 39, 1024001(2019).

    [31] Yuan Y, Jin D, Su L J. Optimization modeling and verification of bidirectional reflectance distribution function for rough surfaces[J]. Laser & Optoelectronics Progress, 55, 052901(2018).

    Lin Fu, Haibo Hong, Xi Wang, Gaobo Xiao, Mingjun Ren. Non-Lambertian Photometric Stereo Vision Based on Inverse Reflectance Model[J]. Acta Optica Sinica, 2020, 40(5): 0520001
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