研究生: |
陳湘宜 Chen, Hsiang-Yi |
---|---|
論文名稱: |
多視角視訊人臉辨識系統 A Multiview Video Face Recognition System |
指導教授: |
楊家輝
Yang, Jar-Ferr |
學位類別: |
碩士 Master |
系所名稱: |
電機資訊學院 - 電腦與通信工程研究所 Institute of Computer & Communication Engineering |
論文出版年: | 2010 |
畢業學年度: | 98 |
語文別: | 中文 |
論文頁數: | 108 |
中文關鍵詞: | 人機互動 、電腦視覺 、人臉辨識 、主成分分析 、線性鑑別分析 |
外文關鍵詞: | human computer interaction, computer vision, face recognition, principal component analysis, linear discriminant analysis |
相關次數: | 點閱:82 下載:0 |
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人機互動(Human-Computer Interaction)近年的蓬勃發展,電腦視覺
(Computer Vision)運用於監視系統上,在我們的生活中也逐漸扮演重要的
角色。針對人臉辨識的研究,本論文分別探討單張人臉影像辨識與視訊
人臉影像辨識的效能及表現,以及使用多視角的人臉視訊影像的資料豐
富性來校正非正臉影像以提高辨識率。
在單張人臉影像辨識環境下,相較於Viola-Jones 人臉偵測器,本論
文首先提出一快速人臉偵測演算法,實驗結果證明我們的方法可提高偵
測速度並有較低的誤判率。然後對於視訊人臉辨識,我們使用多攝影機,
利用特徵臉(Eigenface)、線性鑑別分析(LDA),分析測試影像數量、人臉
角度以及非正臉影像校正後的影像對辨識效能的影響。分別使用AT&T、
Stereo face 人臉資料庫,以及自製的多視角人臉視訊資料庫進行實驗。
Human-computer interaction (HCI), has been rapidly developed in recent
years. Computer vision has been used in surveillance systems, and it
gradually plays an important role in our lives. In the research of face
recognition, in this thesis, we discuss the performance of single-based and
video-based face recognition respectively. To improve the recognition rate, we
use the multi-view video face images to synthesize a virtual frontal face.
In the still image face recognition, in this thesis, we first present a fast face
detector. To compare with the face detector of Viola-Jones, experimental
results show that our method can improve the detection speed and reduce
false alarm rate. For the video-based face recognition, we then use the PCA
and LDA to analyze the number of test images, the different views of face and
the frontal views generated from non-frontal images, which affect the
performance of face recognition. Respectively, we used the AT&T, Stereo face
database and our multi-view face database to do experiments and validations.
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