本篇論文提出了一個基於樣本學習的方法，由一張給定的人臉
相片合成人臉肖像畫素描。整個系統包含了特徵擷取以及合成兩個
模組。在特徵擷取模組部份，我們利用學習過的Active Appearance
Model (AAM)來自動定位人臉的特徵點，接著藉由這些特徵點所提供
的幾何位置，來計算人臉各部位，如眼睛、鼻子、嘴唇等部位之特
徵向量。在合成模組的部份，我們對輸入之人臉相片計算特徵向量
以後，從繪圖庫中找出與其各部位最相似的人臉繪圖零件。最後將
這些繪圖零件、由特徵向量得到的臉部配置參數、以及所選定的髮
型樣板等，加以整合並合成出整體的人臉肖像畫素描。最後提出一
些實驗樣本以顯示此方法的有效性。

This thesis presents an example-based method to
synthesize a human portrait sketch from the given photo. There
are two major modules in the proposed method：the feature
extraction module, and the synthesis module. In the feature
extraction module, we take advantage of the trained Active
Appearance Model (AAM) to automatically extract feature
points from the given example. Then we compute feature
vectors of face components, such as eyes, nose, lip, and so on
according to the geometric positions of feature points. In the
synthesis module, we first compute the feature vectors of the
given photo. Then, based on these feature vectors we find the
most similar drawing component of each face component in the
example database. With these retrieved face components and
user selected hair style, we construct the final human facial
sketch according to the placement parameters obtained from
feature vectors. Several experimental examples are given to
demonstrate the effectiveness of the proposed method.

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