人臉表情合成系統

Facial expression synthesis system

夏華偉(Hua-Wei Hsia)

指導教授 ： 林慧珍

淡江大學/工學院/資訊工程學系碩士班/碩士(2011年)

https://doi.org/10.6846/TKU.2011.00362

摘要

主動式形狀模型是近年來受到關注的一個以模型為基礎的方法，由於它能很成功地將模型校準到非常接近，因而廣泛地被用來解析人臉影像。在傳統的ASM架構，模型是從一組影像集合與其中的相對應的控制點(control points)建構出來，每個控制點的平均算出之後，所有的影像則均依照平均的形狀(mean shape)進行縮放、旋轉以及平移，使得相對應的控制點落在即為接近的位置，變成一組校準(align-ment)的影像，對於人臉偵測、人臉辨識、人臉合成等，其處理效果也較為正確。
本篇論文中提出了一個人臉表情的合成系統，藉由模仿參考的人臉表情影像，利用控制點與ASM在校準後的結果，計算出表情形狀差異(shape difference for expression)做人臉表情合成。
實驗結果顯示，本文所提的人臉表情合成法，對影像中的合成表情效果呈現自然生動，而且可根據使用者的喜好合成不同的表情，具高度的彈性。

關鍵字

主動式形狀模型 ； 表情形狀差異 ； 人臉表情模仿

並列摘要

It is an interesting and challenging problem to synthesis vivid facial expression images. In this paper, we proposed a “facial expression synthesis system” which imitates the reference facial expression image according to the difference between shape feature vectors of the neutral and expression image. Experimental results show vivid and flexible results.

並列關鍵字

Active Shape Model ； shape difference for expression ； imitation of reference expression

參考文獻

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