誇張肖像畫是以誇張與諷刺的手法來表現模特兒的特徵。現今這類畫作比起以寫實手法繪製的肖像畫，更受到大眾的喜愛；但是人們若想要自己模仿繪製出這類的肖像畫，除了要有繪畫天賦之外，也必須經過長時間的繪畫訓練以及對人臉的觀察，才能抓出模特兒的臉部特徵，並用生動的手法誇飾出來。 因此，如果電腦能做到代替誇張肖像畫家的工作，自動模仿繪製出誇張化的卡通肖像畫，將能替人們節省大量的時間及經費。本研究主要在設計一套能誇張肖像畫的系統，以根據使用者輸入的臉部影像，自動擷取臉部的特徵（包括特徵點的相對位置、絕對位置、形狀及大小等），並藉由分析這些特徵與常人相異之處，以一致的方式自動將特徵誇張化。這個系統並能以藝術家的作品為輸入，將使用者的臉部影像轉換成具有畫家卡通風格的誇張肖像畫。除了人臉的效果外，我們也進行了頭髮分離與模擬的研究，以強化畫像風格模擬的完整性。最後，我們以實做出了系統對數個具特徵的人臉影像進行實驗，以驗證其可行性及有效性。 / Caricaturists are good at drawing sketches which express the exaggerated likeness of a person with a bit flavor of humor or sarcasm. People are willing to pay for this kind of work because it requires a lot of practice to achieve excellence. Acute observation is needed to extract the distinct features from the subject, and decent painting skill is essential to depict these features vividly. It will save much time and effort if computers can be trained used to draw caricatures. In this thesis, we developed a system which can extract and analyze facial features from simple an input facial images. The main purpose of this system is to generate the user-own caricature model by exaggerating his/her unique facial features. Different types of features, including relative locations and sizes, absolute locations and sizes, and each the shape of features are all taken in accountwill be considered. Unlike the complex process reported in the literature, we develop a transformative process that can handle different types of features in a more uniform fashion. Using an artist’s finished work as the source image; the proposed system is capable of producing cartoon-like colorful caricatures of a similar style effectively and efficiently. Besides the caricature painting of the face part, we also present some approaches for hair segmentation and hair style painting to increase make the system more the completeness of our system. Finally, we prove the feasibility and effectiveness of our system by showing several experimental results.

本研究嘗試不全以負面假設來看待配戴眼鏡對人臉辨識的影響。吾人將以邊緣偵測圖為基礎，以邊點強度的分析來建立一套定位眼鏡的偵測系統。同時用偵測出的鏡框位置，以邊緣點的強度、密度比較的方式，定位眼睛的位置；並以前述兩套偵測演算，採擷其過程的資訊，進一步地定位鼻子與嘴巴的位置。這些演算形成一個簡易的人臉特徵定位系統，其將可處理配戴眼鏡的人臉；吾人也將進一步地經由其處理過程與結果，分析眼鏡對區域人臉辨識的影響，進而引導出非自然物件可能對人臉辨識的阻礙或輔助。 論文也將以全域比對法中的PCA與ICA演算法作一連串的實驗，剖析眼鏡對於全域辨識的影響；此外，亦用相同的方法來測試非自然物(眼鏡)、光源亮度與人臉角度對於人臉辨識阻礙的程度，以探究是否系統值得花費更大的代價，來移除眼鏡這個被一致認定的人臉辨識障礙，並得以在辨識演算法上獲得更高的效能。 / The objective of this thesis is to investigate the efficacy of face recognition systems when the subjects are wearing glasses. We do not presume that non-facial features such as glasses are nuisances. Instead, we will study whether the inclusion of glasses will have a positive impact on the face detection procedure and how it affects the feature extraction process. We will demonstrate how to use techniques based on local feature analysis to reduce the uncertainties in the matching result due to interferences around the eyes and nose caused by optical glasses. We have also conducted extensive experiments to analyze the effect of glasses on face recognition systems based on global matching strategy. Specifically, we perform both principal component analysis (PCA) and independent component analysis (ICA) on face databases with different percentage of subjects wearing eye glasses. It is concluded that external objects such as glasses will have a negative impact on face recognition using global analysis approaches. However, the adverse influences of illumination and pose are more conspicuous during the recognition process. Therefore, one should take caution when attempting to adapt the global matching scheme to handle the difficulties caused by glasses.

隨著數位影像軟、硬體裝置上進步與普及，普羅大眾對於影像的使用不僅限於日常生活之中，更隨著網路分享概念等Web技術的擴張，這些數量龐大的影像，在使用上更朝向娛樂化、趣味化及個人化的範疇。本論文提出結合影像處理中的人臉特徵分析（Facial Features Analysis）資訊以及影像內容分割（Image Content Segmentation）及影像變形轉換（Image Warping and Morphing）等技術，設計出可以將真實照片中的人臉轉換成為卡通化的肖像，供使用者於各類媒體上使用。卡通化肖像不但具有隱藏影像細節，保留部份隱私的優勢，同時又兼具充份擁有個人化特色的表徵，透過臉部動畫的參數（Facial Animation Parameters）設定，我們提出的卡通化系統更容許使用者依心情，來合成喜、怒、哀、樂等不同表情。另外，運用兩種轉描式（Rotoscoping）及圖像變形（Morphing）法，以不同的合成技巧來解決不同裝置在限定顏色及效果偏好上的各類需求。 / As the acquisition of digital images becomes more convenient, diversified applications of image collections have surfaced at a rapid pace. Not only have we witnessed the popularity of photo-sharing platforms, we have also seen strong demand for novel mechanism that offers personalized and creative entertainment in recent years. In this thesis, we proposed and implemented a personal caricature generator using transformative approaches. By combing facial feature detection, image segmentation and image warping/morphing techniques, the system is able to generate stylized caricature using only one reference image. The system can also produce multiple expressions by controlling the MPEG-4 facial animation parameters (FAP). Specifically, by referencing to various pre-drawn caricature in our database as well as feature points for mesh creation, personalized caricatures are automatically generated from the real photos using either rotoscoping or transformative approaches. The resulting caricature can be further modified to exhibit multiple facial expressions. Important issues regarding color reduction and vectorized representation of the caricature have also been discussed in this thesis.