【摘要】：隨著社會信息化進程加快和計算機識別等技術的迅速發(fā)展,如何創(chuàng)建更具有真實感的三維人臉模型成為了一個非常具有挑戰(zhàn)性的問題。三維人臉模型的重建在虛擬現(xiàn)實、視頻監(jiān)控、三維動畫和人臉識別等領域都有著越來越多的應用。在身份識別方面,與其他生物識別相比較,人臉識別具有采集方便,可用性強等顯著優(yōu)勢,受到大量關注。相對于二維人臉圖像更容易受外部因素干擾,三維人臉模型不易受到外界光照條件、和化妝等因素的影響。因此,基于三維人臉重建模型的人臉識別技術能夠更好的提高識別的準確度。在三維動畫和游戲建模方面,創(chuàng)建更有真實感的模型成為了一個熱點方向,現(xiàn)在,三維人臉重建己經逐步成為計算機視覺與計算機輔助設計等領域中備受關注的熱點研究問題。不管是從理論研究還是從實際應用的方面來看,三維人臉重建都是值得深入研究的,它對于推動計算機視覺和計算機輔助設計研究的發(fā)展都有著重要的意義。但是目前的曲線曲面重建算法仍然存在很多問題:(1)當對擬合精度要求低的時候,很多局部上的極小值點就會很容易被忽略,會導致最后得到的曲線在該點出現(xiàn)形變;(2)當對擬合精度要求高的時候,計算量往往會變得十分龐大。針對上述問題,本文的研究內容主要包括以下幾個方面:(1)點云數(shù)據(jù)預處理。三維人臉數(shù)據(jù)通常都是通過激光掃描儀獲取的大量點云數(shù)據(jù)。這些數(shù)據(jù)不可避免地會受到噪聲的污染,所以在進行曲面重建之前對點云數(shù)據(jù)進行簡單的降噪處理。(2)提出一種新的曲線重建算法。通過對經典重建算法的分析,我們依據(jù)曲線的幾何特征點和受誤差約束的次要關鍵點在曲線重建中的重要程度,對這兩類關鍵點進行分層,進而在保證精度的前提下提高了算法的工作效率。(3)曲面重建算法及在三維人臉重建中的應用。基于點、線、面的重要思想,對具有行列特征的數(shù)據(jù)點進行分割來獲取曲面的輪廓線的數(shù)據(jù)點列,再采用特征分層的曲線重建算法,在斜高差,弓高差的約束條件下進行曲面擬合。并將此曲面重建算法應用于三維人臉曲面的重建。
[Abstract]:With the rapid development of social information technology and computer recognition technology, how to create a more realistic 3D face model has become a very challenging problem. 3D face model reconstruction has more and more applications in virtual reality, video surveillance, 3D animation and face recognition. In the aspect of identity recognition, compared with other biometrics, face recognition has many advantages, such as convenient collection, strong usability and so on. Compared with two-dimensional face images, 3D face models are more susceptible to external interference, and 3D face models are not easily affected by external illumination conditions, makeup and other factors. Therefore, face recognition based on 3D face reconstruction model can improve the accuracy of recognition. In the field of 3D animation and game modeling, creating more realistic models has become a hot topic. Now, 3D face reconstruction has gradually become a hot research issue in computer vision and computer-aided design and other fields. From both theoretical and practical aspects, 3D face reconstruction is worthy of further study. It is of great significance to promote the development of computer vision and computer-aided design (CAD) research. However, there are still many problems in the current curve and surface reconstruction algorithms: (1) when the precision of fitting is low, many local minimum points are easily ignored. The resulting curve will deform at this point; (2) when the precision of fitting is high, the computation will become very large. To solve the above problems, this paper mainly includes the following aspects: (1) Point cloud data preprocessing. 3D face data are usually a large number of point cloud data obtained by laser scanner. These data will inevitably be polluted by noise, so the point cloud data is simply de-noised before surface reconstruction. (2) A new curve reconstruction algorithm is proposed. Based on the analysis of the classical reconstruction algorithm, we stratify the two key points according to the importance of the geometric feature points of the curve and the minor key points constrained by errors in the reconstruction of the curve. Furthermore, the efficiency of the algorithm is improved on the premise of ensuring accuracy. (3) Surface reconstruction algorithm and its application in 3D face reconstruction. Based on the important idea of point, line and surface, the data points with column and column feature are segmented to obtain the data points of the contour line of the curved surface, and then the curve reconstruction algorithm of feature stratification is adopted, and the deviation of oblique height is obtained. The curved surface fitting is carried out under the constraint of bow height difference. The surface reconstruction algorithm is applied to 3D face surface reconstruction.
【學位授予單位】：山東師范大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41

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