| Summary: | 碩士 === 國立成功大學 === 電腦與通信工程研究所 === 98 === 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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