A review on data-driven learning of a talking head model
by Kyaw Kyaw Htike
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 16, No. 2, 2017

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.

Online publication date: Sun, 21-May-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Systems Technologies and Applications (IJISTA):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com