| Summary: | 碩士 === 國立交通大學 === 多媒體工程研究所 === 102 === Face recognition has been studied for many years, but it has stayed a challenging problem as no one perfect method has been proposed. Most face recognition algorithms are image-based. However, in many cases, it is useful and beneficial to apply face recognition algorithms to video data rather than single images.
Compared to a single image, a video can provide more information, thus improving the reliability of face recognition. This thesis focuses on facial image sequence similarity as the main research topic. We compare four different datasets under several different environments to analyze algorithm for computing face image sequence similarities. We illustrate the pros and cons of each method and also discuss several factors that may affect the performance. In addition, we also analyze the characteristics of these data sets.
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