此次論文，用了許多影像處理技巧，有平均低通濾波器、Sobel高通濾波器、影像灰階轉換、小波轉換等，可常見於國內外影像方面論文，對於影像方面研究是必備的基礎知識。

本篇論文定位方法主要有動態物件偵測、人臉膚色分析與橢圓樣板定位人臉，主要針對動態影像，快速定位人臉。辨識採用統計的方式，主要將資料庫中，同一人不同表情的視為同一類，利用LDA(Linear Discriminant Analysis)線性鑑別式分析，將不同類的人距離拉開，並拉近同一類的人，亦即將資料庫樣本全部分類到新的向量空間中，然後再將待測人臉投影到此新的向量空間中，以歐式距離計算出與空間中哪類最接近，來判斷是否為同一類裡的同一個人。

This thesis was built by using many important image processing technologies such as average filter, Sobel high-pass filter, gray-level transform, and wavelet, etc. Those technologies are basic knowledge through image processing which can be seen in many papers.

This thesis proposed a fast face detection method using active object detection, face skin color analysis, and elliptical template. This method was built by statistical learning theory which using Linear Discriminant Analysis (LDA) to separate different faces. That is, it classifies all patterns in database into new vector space by LDA algorithm. After that, the proposed method will decides whether the tester is in the same class by calculating the Euclidean distance between the tester vector and the training vectors.

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