This term has connotations in the context of practical work in artificial intelligence, as well as for theoretical studies of A.I. and the philosophy of mind. In the current article we are primarily concerned with the former usage of the term, namely with that domain of approaches to machine intelligence which do not take, as a primary goal, an attempt to match or exceed human intelligence, this latter goal being the hallmark of “strong A.I.” research.
Published in Chapter:
Facial Expression Analysis, Modeling and Synthesis: Overcoming the Limitations of Artificial Intelligence with the Art of the Soluble
Christoph Bartneck (Eindhoven University of Technology, The Netherlands) and Michael J. Lyons (Ritsumeikan University, Japan)
Copyright: © 2009
|Pages: 22
DOI: 10.4018/978-1-60566-354-8.ch003
Abstract
The human face plays a central role in most forms of natural human interaction so we may expect that computational methods for analysis of facial information, modeling of internal emotional states, and methods for graphical synthesis of faces and facial expressions will play a growing role in human-computer and human-robot interaction. However, certain areas of face-based HCI, such as facial expression recognition and robotic facial display have lagged others, such as eye-gaze tracking, facial recognition, and conversational characters. Our goal in this paper is to review the situation in HCI with regards to the human face, and to discuss strategies, which could bring more slowly developing areas up to speed. In particular, we are proposing the “The Art of the Soluble” as a strategy forward and provide examples that successfully applied this strategy.