Abstract摘要
In this paper, a new technique for modeling textured 3D faces is introduced. 3D faces can either be generated automatically from one or more photographs, or modeled directly through an intuitive user interface. Users are assisted in two key problems of computer aided face modeling. First, new face images or new 3D face models can be registered automatically by computing dense one-to-one correspondence to an internal face model. Second, the approach regulates the naturalness of modeled faces avoiding faces with an “unlikely” appearance.
本文介紹了一種新的三維紋理人臉建模技術。三維面可以從一張或多張照片自動生成，也可以通過直觀的用戶界面直接建模。計算機輔助人臉建模的兩個關鍵問題是輔助用戶。首先，通過計算與內部人臉模型的密集一一對應關系，可以自動注冊新的人臉圖像或新的三維人臉模型。其次，該方法規范了模擬人臉的自然性，避免了具有“不太可能”外觀的人臉。
Starting from an example set of 3D face models, we derive a morphable face model by transforming the shape and texture of the examples into a vector space representation. New faces and expressions can be modeled by forming linear combinations of the prototypes. Shape and texture constraints derived from the statistics of our example faces are used to guide manual modeling or automated matching algorithms.
從一組三維人臉模型的實例出發，通過將實例的形狀和紋理轉化為矢量空間表示，得到了一個可變形的人臉模型。新的面和表達式可以通過形成原型的線性組合來建模。從我們的示例面統計信息中導出的形狀和紋理約束用於指導手動建模或自動匹配算法。
We show 3D face reconstructions from single images and their applications for photo-realistic image manipulations. We also demonstrate face manipulations according to complex parameters such as gender, fullness of a face or its distinctiveness.
我們展示了由單個圖像重建的三維人臉及其在照片真實感圖像處理中的應用。我們還展示了根據復雜的參數，如性別，面部豐滿度或其獨特性的面部操作。
1 Introduction
Computer aided modeling of human faces still requires a great deal of expertise and manual control to avoid unrealistic, non-face-like results. Most limitations of automated techniques for face synthesis, face animation or for general changes in the appearance of an individual face can be described either as the problem of finding corresponding feature locations in different faces or as the problem of separating realistic faces from faces that could never appear in the real world. The correspondence problem is crucial for all morphing techniques, both for the application of motion-capture data to pictures or 3D face models, and for most 3D face reconstruction techniques from images. A limited number of labeled feature points marked in one face, e.g., the tip of the nose, the eye corner and less prominent points on the cheek, must be located precisely in another face. The number of manually labeled feature points varies from
計算機輔助人臉建模仍然需要大量的專業知識和手動控制，以避免不現實的、非人臉的結果。用於人臉合成、人臉動畫或單個人臉外觀的一般變化的自動化技術的大多數局限性可以描述為在不同的人臉中找到相應的特征位置的問題，或者描述為將真實的人臉與現實世界中永遠不會出現的面分離的問題。無論是對於將運動捕捉數據應用於圖片或三維人臉模型，還是對於大多數基於圖像的三維人臉重建技術，對應問題對於所有變形技術都是至關重要的。在一張臉上標記的有限數量的標記特征點，例如鼻尖、眼角和臉頰上不太突出的點，必須精確地位於另一張臉上。手動標記的特征點的數目從