Non-Lambertian Photometric Stereo For 3D Reconstruction

Reconstructing the shape and reflectance of an object from images is a significant task in computer vision and graphics that has led to a variety of applications including virtual reality,inverse engineering,and cultural relics protection.However,most of the image-based 3D reconstruction methods can not be applied to specular objects,i.e.plastics,porcelain,or Chinese jade.It is practical and valuable to focuse on acquiring the shape and reflectance of non-Lambertian objects.Most image-based 3D reconstruction methods,i.e.structured light and stereo matching,fail on the texture-less surfaces due to the lack of image features.The classic photometric stereo problem assumes a Lmabertian surface reflectance model and recovers per-pixel normal maps without relying on image features.However,the real-world is full of non-Lambertian objects,covering various surface materials.It is a significant challenge to recover surface shapes and reflectance of non-Lambertian objects.Considering the above challenges,the thesis is about the most widely existed high-lights in daily life and carrys out researches on the 3D reconstruction of non-Lambertian objects.In this thesis,we relax constraints of lightings and reflectance models of classic photometric stereo.High detailed surfaces are reconstructed by combining with other3 D reconstruction methods.In addition,we build the scanning setup for photometric stereo and quantitatively evaluate state-of-the-art multi-view photometric stereo on a newly collected benchmark dataset,which is publicly available for inspiring future re-search.Specifically,the main innovations and work of this article can be summarized as follows:1.When performing 3D reconstruction from the normal estimated from photomet-ric stereo,the 3D model contains high-frequency details while the geometry is distorted due to the existence of highlights.In this thesis,we present a convex framework to acquire high resolution surfaces.It is typical to couple a structure-light setup and a photometric method to reconstruct a high resolution 3D surface.We derived a global optimizer to fuse high frequency details and low frequency geometry information for preventing the solution stuck in a local minima.We develop a convex variational model by incorporating a total variation(TV)reg-ularization term with a data term to generate the surface.Through relaxing the model to an equivalent high dimensional variational problem,we obtain a global minimizer of the proposed problem.Results on both synthetic and real-world data show an excellent performance by utilizing our convex variational model.2.Most photometric stereo methods discard specular outliers directly in order to meet the Lambertian assumption.Although the complexity of the algorithm is simpli-fied,it cannot deal with the common specular reflection in real life effectively and cannot obtain surface reflection correctly.The thesis presented a new method based on dichromatic model aiming to solve the non-Lambertian surface normal and reflectance by making full use of the diffuse and specular components.We separate the diffuse component and the specular component based on the dicromat-ical model by a linear optimization.The diffuse component is utilized to compute surface normals while the highlight is employed to improve the accuracy of the estimated surface normals and reflectance.The experimental results demonstrate that the method is effective to improve the accuracy of the surface normal and reflectance.3.The classic photometric stereo assumes a Lambertian model,a fixed camera,and known directional illuminations to compute the normal map from multiple images,only reconstructing parts of the 3D model.Most proposed photometric stereo methods are still limited to the laboratory environment,so it is a huge challenge to apply the method into real life.The thesis presents a method to capture 3D shape with a multi-view photometric stereo technique under relaxed lighting conditions.The capture setup we proposed in this thesis works for general isotropic materi-als.To eliminate the effects of the near-light and perspective camera condition,a block based strategy is proposed after thorough analysis on lighting distributions and setup calibrations.The experimental results prove that the block based strat- egy can eliminate the near-light and perspective camera model effects and improve the quality of the reconstructed 3D model obviously.In addition,we also quantita-tively evaluate state-of-the-art multi-view photometric stereo on a newly collected benchmark dataset,which is publicly available for inspiring future research.