Title: A review on data-driven learning of a talking head model

Authors: Kyaw Kyaw Htike

Addresses: School of Information Technology, UCSI University, 56000 Kuala Lumpur, Malaysia

Abstract: Constructing a talking head model of a person allows generation of a novel talking face animation from an unseen audio sequence of the person. This has important applications such as building virtual avatars of people that can interact with real people in novel situations, model-based video compression, teleconferencing, human-computer interaction, computer graphics and video games. Traditionally, talking head models have been built by manual painstaking work. The advancement of computer vision and machine learning techniques, especially in the past decade, has made possible the automatic learning of a talking head model of a person from data. In this paper, we focus on this area of machine learning based data-driven facial animation and critically review the most common approaches, compare and contrast among them and identify promising research directions and prospects.

Keywords: audio-driven facial motion synthesis; facial animation; animated speech; virtual avatar; talking face; audio-visual correlation.

DOI: 10.1504/IJISTA.2017.084239

International Journal of Intelligent Systems Technologies and Applications, 2017 Vol.16 No.2, pp.169 - 190

Received: 18 Apr 2016
Accepted: 01 Dec 2016
Published online: 21 May 2017 *

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