基于光度立体技术的三维形状重构
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摘要
为实现复杂光环境下目标物体的准确三维重构,增加光度立体技术应用的灵活性,提出一种基于光度立体技术的改进算法来估算物体表面的反照率和三维形状。需要通过标定球校准出光源系统的方向参数,利用球谐模型代替朗伯表面模型,计算目标物体表面的反射率和法向量,基于全局积分算法,由法向量恢复物体表面的三维形状信息。比较传统光度立体技术的实现策略,该方法具有误差小、鲁棒性好的优点。
An improved algorithm based on photometric stereo technology was proposed to estimate the albedo and the shape of the object surface for realizing the accurate 3 Dreconstruction of the target object in the complex light environment and increasing the flexibility of the application of the photometric stereo technology.The direction parameters of the light source system needed to be calibrated by calibrating the ball.The albedo and normal vectors of the object surface were calculated using the spherical harmonic model instead of the Lambert surface model.The 3 Dshape information of the surface was recovered from the normal vector based on the global integration algorithm.The method has the advantages of small error and good robustness compared with the implementation strategy of traditional photometric stereo technology.
An improved algorithm based on photometric stereo technology was proposed to estimate the albedo and the shape of the object surface for realizing the accurate 3 Dreconstruction of the target object in the complex light environment and increasing the flexibility of the application of the photometric stereo technology.The direction parameters of the light source system needed to be calibrated by calibrating the ball.The albedo and normal vectors of the object surface were calculated using the spherical harmonic model instead of the Lambert surface model.The 3 Dshape information of the surface was recovered from the normal vector based on the global integration algorithm.The method has the advantages of small error and good robustness compared with the implementation strategy of traditional photometric stereo technology.
引文
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[3]CAO Wen.The application research of image-based modeling in reverse engineering[D].Dalian:Dalian University of Technology,2015(in Chinese).[曹文.基于图像的三维重建在逆向工程中的应用研究[D].大连:大连理工大学,2015.]
[4]PAN Liang,LI Ruihai.Analysis of the application of 3Dreconstruction technology based on image in film and television production[C]//Chinese Academy of Photoreceptor Academic Annual Meeting,2016(in Chinese).[潘亮,李瑞海.基于图像的三维重建技术在影视制作中的运用浅析[C]//中国感光学会学术年会,2016.]
[5]Ahmad J,Sun J.An improved photometric stereo through distance estimation and light vector optimization from diffused maxima region[J].Pattern Recognition Letters,2014,50(1):15-22.
[6]Xie Limin,Song Zhan,Huang Xinhan.A novel method for the calibration of an LED-based photometric stereo system[C]//IEEE International Conference on Information&Automation,2013:780-783.
[7]Ackermann J,Langguth F,Fuhrmann S,et al. Multi-view photometric stereo by example[C]//International Conference on 3dVision,2014:259-266.
[8]Matsumoto A,Saito H,Ozawa S.3Dreconstruction of skin surface from photometric stereo images with specular reflection and interreflection[J].Electrical Engineering in Japan,2015,129(3):51-58.
[9]XIE Limin.Research on photometric stereo algorithm based on near-field lighting[D].Wuhan:Huazhong University of Science&Technology,2015(in Chinese).[谢利民.基于近场照明的光度立体视觉算法研究[D].武汉:华中科技大学,2015.]
[10]Schnieders D,Wong KYK.Camera and light calibration from reflections on a sphere[J].Computer Vision&Image Understanding,2013,117(10):1536-1547.
[11]YANG Xin,LI Rundong,WANG Guanbo,et al.Study on unfolding algorithms for neutron depth profiling[J].Chinese Journal of Computational Physics,2017,34(5):603-610(in Chinese).[杨鑫,李润东,王冠博,等.中子深度分析反演算法研究[J].计算物理,2017,34(5):603-610.]
[12]WANG Jianlun,HAN Yu,HE Jianlei,et al.A 3Dreconstruction method based on single 2D image[P].China:CN103824323A,2014(in Chinese).[王建仑,韩彧,何建磊,等.一种基于单幅二维图像的三维重建方法[P].中国:CN103824323A,2014.]
[13]Volegov PL,Danly CR,Fittinghoff D,et al.Three-dimensional reconstruction of neutron,gamma-ray,and x-ray sources using spherical harmonic decomposition[J].Journal of Applied Physics,2017,122(17):175-190.
[14]XIAO Qingmei.Research on improved RBF neural network algorithm based on LM[D].Chongqing:Southwest University,2016(in Chinese).[肖清湄.基于LM改进的RBF神经网络算法研究[D].重庆:西南大学,2016.]
[15]Harker M,O’Leary P.Regularized reconstruction of a surface from its measured gradient field[J].Journal of Mathematical Imaging&Vision,2013,51(1):1-25.