本文選題：三維可視化　切入點：統(tǒng)計模型　出處：《電子科技大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：目前，三維人臉可視化技術(shù)廣泛應(yīng)用于三維游戲、三維動漫以及安防等領(lǐng)域中。因此，該技術(shù)在眾多研究領(lǐng)域中一直受到專家學(xué)者們的重視，尤其是計算機(jī)圖形學(xué)、模式識別等領(lǐng)域。其中基于單幅人臉照片的三維可視化方法，能夠在有效避免三維可視化需要耗費大量人力物力的問題的同時，實現(xiàn)較好的三維可視化效果。因此該項技術(shù)的研究具有重大意義。 單幅人臉的三維可視化方法眾多，目的在于建立與照片中人臉一致的三維人臉模型。其中基于統(tǒng)計學(xué)習(xí)的方法，主要是通過PCA建立可以形變的統(tǒng)計模型獲得人臉的三維形狀，并采用正交投影的方法來進(jìn)行紋理映射。本文在此基礎(chǔ)上進(jìn)行研究，，完成了以下幾個方面的工作： 一、三維人臉樣本庫統(tǒng)一過程中三角網(wǎng)格的統(tǒng)一 統(tǒng)一三維人臉庫的人臉結(jié)構(gòu)是整個基于統(tǒng)計學(xué)習(xí)方法的基礎(chǔ)，通常情況下，人臉樣本點之間的對應(yīng)備受關(guān)注，而三角網(wǎng)格的對應(yīng)卻很少被提及，本文提出一種三維人臉樣本之間三角網(wǎng)格的統(tǒng)一方法，利用原始人臉樣本庫中的三角網(wǎng)格，通過跟蹤其在點對應(yīng)時的各種變換，進(jìn)而得出點對應(yīng)后的三角網(wǎng)格連接。經(jīng)過處理，整個三維人臉樣本間具有統(tǒng)一的連接方式，方便后續(xù)環(huán)節(jié)進(jìn)一步的處理； 二、形狀模型構(gòu)建過程中能量函數(shù)的求解方法。 在構(gòu)建模型的測試階段中，平均模型與人臉照片之間的匹配問題可轉(zhuǎn)化為最小化兩者之間距離的能量函數(shù)。為避免能量函數(shù)的解出現(xiàn)過擬合現(xiàn)象，本文利用l1范數(shù)正則化項對能量函數(shù)進(jìn)行約束，使解出的人臉模型在絕大多數(shù)情況下匹配照片中的人臉。但是相比利用先驗知識作為約束的求解方法，本文方法仍然存在許多不足之處。 三、提出兩種特征點深度估計方法，并利用估計特征點提高模型的準(zhǔn)確性。 從人臉模型的側(cè)面觀察角度出發(fā)，本文提出了兩種特征點深度估計的方法：近鄰加權(quán)法和稀疏表示法，并利用估計的三維特征點進(jìn)行建模，提高建模精度，使得構(gòu)建的人臉模型更符合真實照片中人臉的形態(tài)； 四、基于分割模板的紋理映射方法。 在紋理映射中，基于約束點控制的紋理映射往往存在背景殘留等現(xiàn)象，本文通過對測試人臉照片進(jìn)行分割，對所得的分割結(jié)果進(jìn)行腐蝕處理得到一個安全區(qū)域的掩膜，利用該掩膜對映射有誤的地方進(jìn)行修正，改善紋理映射的效果。
[Abstract]:At present, 3D face visualization technology is widely used in the fields of 3D game, 3D animation and security. Therefore, the technology has been paid attention to by experts and scholars in many research fields, especially computer graphics. In the field of pattern recognition, 3D visualization method based on single face image can effectively avoid the problem that 3D visualization needs a lot of manpower and material resources. Therefore, the research of this technology is of great significance. There are many 3D visualization methods for single face, the purpose of which is to build a 3D face model consistent with the face in the photograph, in which, based on the statistical learning method, the statistical model can be constructed by PCA to obtain the 3D shape of the face. The method of orthogonal projection is used to carry out texture mapping. The first is the unification of triangular mesh in the process of 3D face sample database unification. The face structure of the unified 3D face database is the basis of the whole statistical learning method. Usually, the correspondence between face sample points is paid close attention to, but the correspondence of triangular mesh is seldom mentioned. In this paper, a unified method of triangulation mesh between 3D face samples is proposed. By tracking the various transformations of the triangulated mesh in the primitive human face sample database, the triangular mesh connection after the point correspondence can be obtained. After processing, the triangulation mesh after the point correspondence can be obtained by using the triangulation mesh in the primitive human face sample database. The whole 3D face sample has a unified connection mode, which is convenient for further processing. Second, the method of solving the energy function in the process of shape model construction. In the test stage of constructing the model, the matching problem between the average model and the face photograph can be transformed into an energy function that minimizes the distance between the two models. In this paper, the energy function is constrained by the L 1 norm regularization term, so that the solved face model matches the face in the photo in most cases, but compared with the prior knowledge as the constraint method, There are still many shortcomings in this method. Thirdly, two methods of depth estimation of feature points are proposed, and the accuracy of the model is improved by using the estimation of feature points. From the side view of face model, this paper presents two methods of depth estimation of feature points: nearest neighbor weighted method and sparse representation method, and use the estimated 3D feature points to model to improve the modeling accuracy. Make the constructed face model more consistent with the face shape in the real photos; Fourth, texture mapping method based on segmentation template. In texture mapping based on constraint point control texture mapping often exists some phenomena such as background residue. In this paper a mask of a safe area is obtained by segmentation of test face images and corrosion of the resulting segmentation results. The mask is used to correct the mapping errors to improve the effect of texture mapping.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP391.41

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