Intelligent interface agents for biometric applications

This thesis investigates the benefits of applying the intelligent agent paradigm to biometric identity verification systems. Multimodal biometric systems, despite their additional complexity, hold the promise of providing a higher degree of accuracy and robustness. Multimodal biometric systems are examined in this work leading to the design and implementation of a novel distributed multi-modal identity verification system based on an intelligent agent framework. User interface design issues are also important in the domain of biometric systems and present an exceptional opportunity for employing adaptive interface agents. Through the use of such interface agents, system performance may be improved, leading to an increase in recognition rates over a non-adaptive system while producing a more robust and agreeable user experience. The investigation of such adaptive systems has been a focus of the work reported in this thesis. The research presented in this thesis is divided into two main parts. Firstly, the design, development and testing of a novel distributed multi-modal authentication system employing intelligent agents is presented. The second part details design and implementation of an adaptive interface layer based on interface agent technology and demonstrates its integration with a commercial fingerprint recognition system. The performance of these systems is then evaluated using databases of biometric samples gathered during the research. The results obtained from the experimental evaluation of the multi-modal system demonstrated a clear improvement in the accuracy of the system compared to a unimodal biometric approach. The adoption of the intelligent agent architecture at the interface level resulted in a system where false reject rates were reduced when compared to a system that did not employ an intelligent interface. The results obtained from both systems clearly express the benefits of combining an intelligent agent framework with a biometric system to provide a more robust and flexible application

Utilizing Bayesian Techniques for User Interface Intelligence

The purpose of this research is to study the injection of an intelligent agent into modern user interface technology. This agent is intended to manage the complex interactions between the software system and the user, thus making the complexities transparent to the user. The background study will show that while interesting and promising research exists in the domain of intelligent interface agents, very little research has been published that indicates true success in representing the uncertainty involved in predicting user intent. The interface agent architecture presented in this thesis will offer one solution for solving the problem using a newly developed Bayesian-based agent called the Intelligent Interface Agent (IIA). The proof of concept of this architecture has been implemented in an actual expert system, and this thesis presents the results of the implementation. The conclusions of this thesis will show the viability of this new agent architecture, as well as promising future research in examination of cognitive models, development of an intelligent interface agent interaction language, expansion of meta-level interface learning, and refinement of the PESKI user interface

Reviews

Researching into Teaching Methods in Colleges and Universities by Clinton Bennett, Lorraine Foreman‐Peck and Chris Higgins, London: Kogan Page, 1996. ISBN: 0–7494–1768–4, 136 (+ vii) pages, paperback. £14.99

Affect and Metaphor Sensing in Virtual Drama

We report our developments on metaphor and affect sensing for several metaphorical language phenomena including affects as external entities metaphor, food metaphor, animal metaphor, size metaphor, and anger metaphor. The metaphor and affect sensing component has been embedded in a conversational intelligent agent interacting with human users under loose scenarios. Evaluation for the detection of several metaphorical language phenomena and affect is provided. Our paper contributes to the journal themes on believable virtual characters in real-time narrative environment, narrative in digital games and storytelling and educational gaming with social software

A Decision Theoretic Approach for Interface Agent Development

The complexity of current software applications is overwhelming users. The need exists for intelligent interface agents to address the problem of increasing taskload that is overwhelming the human user. Interface agents could help alleviate user taskload by extracting and analyzing relevant information, and providing information abstractions of that information, and providing timely, beneficial assistance to users. These agents could communicate with the user through the existing user interface and also adapt to user needs and behaviors. Central to providing assistance to a user is the issue of correctly determining the user\u27s intent. This dissertation presents an effective, efficient, and extensible decision-theoretic architecture for user intent ascription. The multi-agent architecture, the Core Interface Agent architecture, provides a dynamic, uncertainty-based knowledge representation for modeling the inherent ambiguity in ascribing user intent. The knowledge representation, a Bayesian network, provides an intuitive, mathematically sound way of determining the likelihood a user is pursuing a goal. This likelihood, combined with the utility of offering assistance to the user, provides a decision-theoretic approach to offering assistance to the user. The architecture maintains an accurate user model of the user\u27s goals within a target system environment. The on-line maintenance of the user model is performed by a collection of correction adaptation agents. Because the decision-theoretic methodology is domain-independent, this new methodology for user intent ascription is readily extensible over new application domains. Furthermore, it also offers the ability to bootstrap intent understanding without the need for often lengthy and costly knowledge elicitation. Thus, as a side benefit, the process can mitigate the classic knowledge acquisition bottleneck problem

The inaccuracy and insincerity of real faces

Since conversation is a central human activity, the synthesis of proper conversational behavior for Virtual Humans will become a critical issue. Facial expressions represent a critical part of interpersonal communication. Even with the most sophisticated, photo-realistic head model, an avatar who's behavior is unbelievable or even uninterpretable will be an inefficient or possibly counterproductive conversational partner. Synthesizing expressions can be greatly aided by a detailed description of which facial motions are perceptually necessary and sufficient. Here, we recorded eight core expressions from six trained individuals using a method-acting approach. We then psychophysically determined how recognizable and believable those expressions were. The results show that people can identify these expressions quite well, although there is some systematic confusion between particular expressions. The results also show that people found the expressions to be less than convincing. The pattern of confusions and believability ratings demonstrates that there is considerable variation in natural expressions and that even real facial expressions are not always understood or believed. Moreover, the results provide the ground work necessary to begin a more fine-grained analysis of the core components of these expressions. As some initial results from a model-based manipulation of the image sequences shows, a detailed description of facial expressions can be an invaluable aid in the synthesis of unambiguous and believable Virtual Humans

An intelligent interface agent for an airline company web portal

In this paper we introduce an implementation of an Intelligent Interface Agent to support the use of a web portal in an airline company. The interface agent architecture and data model is presented. We formalized concepts such as relevance and proximity regarding the data structure. The concepts of personal opinion and general opinion are also introduced and formalized. A statistical analysis was performed to obtain the best value when processing the general opinion. Some results of that analysis are presented and we conclude discussing our work and presenting future improvements