Modeling Facial Ageing Process with Face Appearance Model
碩士 === 國立臺灣師範大學 === 資訊教育研究所 === 90 === This thesis proposes a method for modeling of the facial ageing process. Face appearance model (FAM) is used to model the shape and texture variations of human faces. Fuzzy c-means clustering is applied to group faces in the training set that have si...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2002
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| Online Access: | http://ndltd.ncl.edu.tw/handle/27193916973743158800 |
| Summary: | 碩士 === 國立臺灣師範大學 === 資訊教育研究所 === 90 === This thesis proposes a method for modeling of the facial ageing process. Face appearance model (FAM) is used to model the shape and texture variations of human faces. Fuzzy c-means clustering is applied to group faces in the training set that have similar face appearances. Group face appearance models (group FAM) are built to model the unique variations of face appearance within each group. Ageing function is defined by the model parameters of each individual in different ages. The simulated results are obtained by applying the most typical model parameters of the simulated age to group FAMs. Experimental results showed that using group FAMs can better simulate facial ageing process than the usual face appearance model in terms of both visual perceptions and mathematical similarity measures.
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