Dimensionality reduction for computer facial animation

This paper describes the usage of dimensionality reduction techniques for computer facial animation. Techniques such as Principal Components Analysis (PCA), Expectation–Maximization (EM) algorithm for PCA, Multidimensional Scaling (MDS), and Locally Linear Embedding (LLE) are compared for the purpos...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Tsai, Flora S.
مؤلفون آخرون: School of Electrical and Electronic Engineering
التنسيق: مقال
اللغة:English
منشور في: 2013
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/84786
http://hdl.handle.net/10220/11106
الوسوم: إضافة وسم
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المؤسسة: Nanyang Technological University
اللغة: English
الوصف
الملخص:This paper describes the usage of dimensionality reduction techniques for computer facial animation. Techniques such as Principal Components Analysis (PCA), Expectation–Maximization (EM) algorithm for PCA, Multidimensional Scaling (MDS), and Locally Linear Embedding (LLE) are compared for the purpose of facial animation of different emotions. The experimental results on our facial animation data demonstrate the usefulness of dimensionality reduction techniques for both space and time reduction. In particular, the EMPCA algorithm performed especially well in our dataset, with negligible error of only 1–2%.