A virtual salesperson

This chapter describes the use of a graphical humane interface - a Virtual Salesperson. The face of the Virtual Salesperson is a generic Facial Animation Engine developed at the University of Genova in Italy and uses a 3-D computer graphics model based on the MPEG-4 standard supplemented by Cyberware scans for facial detail. The appearance of the head may be modified by Facial Definition Parameters to more accurately model the required visage allowing one model to represent many different Talking Heads. The “brain” of the Virtual Salesperson, developed at Curtin University, integrates natural language parsing, text to speech synthesis, and artificial intelligence systems to produce a “bot” capable of helping a user through a question/answer sales enquiry. The Virtual Salesperson is a specific example of a generic Human Computer Interface - a Talking Head.

Mathematics in microworlds: showing the flag!

This article presents an overview of how to use Logo programming to draw national flags. This activity moves away from overt geometry to implicit geometry.

Painting that moves : digital realism and the single moving image

Explores space and object relations in a digital 3-D animation production, "Moving-Image". The exegesis examines these relations through an analysis of pictorial realism in painting. The illusion of three dimensional forms in the space of the computer screen is contextualised by investigation of the work's underlying digital conditions.

Super-realistic rendering using real-time tweening

The realism of contemporary computer graphics (and especially Virtual Reality {VR}) is limited by the great computational cost of rendering objects of appropriate complexity with convincing lighting and surface effects. We introduce a framework that allows rendering of objects in true photographic quality using tweening. The simple but effective design of our system allows us not only to perform the necessary operations in real-time on standard hardware, but also achieve other effects like morphing. Furthermore, it is shown how our system can be gainfully employed in non-VR contexts like extreme low-bandwidth video-conferencing and others.

Simulating crowd phenomena in African markets

Crowd simulation is an important feature in the computer graphics field. Typical implementations simulate battle scenes, emergency situations, safety issues or add content to virtual environments. The problem stated in this paper falls in the last category. We present a crowd simulation behavioural model which allows us to simulate identified phenomena in popular local African markets such as narrow street flows and crowd formation around street performances. We propose a three-tier architecture model enable to produce intentions, perform path planning and control movement. We demonstrate that this approach produces the desired behaviour associated with crowds in an African market, which includes navigation, flow formation and circle creation.

Automating the creation of 3D animation from annotated fiction text

This paper describes a strategy for automatically converting fiction text into 3D animations. It assumes the existence of fiction text annotated with avatar, object, setting, transition and relation annotations, and presents a transformation process that converts annotated text into quantified constraint systems, the solutions to which are used in the population of 3D environments. Constraint solutions are valid over temporal intervals, ensuring that consistent dynamic behaviour is produced. A substantial level of automation is achieved, while providing opportunities for creative manual intervention in animation process. The process is demonstrated using annotated examples drawn from popular fiction text that are converted into animation sequences, confirming that the desired results can be achieved with only high-level human direction.

A method for automatically creating 3D animated scenes from annotated fiction text

This paper describes a strategy for automatically converting fiction text into 3D animations. It assumes the existence of fiction text annotated with avatar, object, setting, transition and relation annotations, and presents a transformation process that converts annotated text into quantified constraint systems, the solutions to which are used in the population of 3D environments. Constraint solutions are valid over temporal intervals, ensuring that consistent dynamic behaviour is produced. A substantial level of automation is achieved, while providing opportunities for creative manual intervention in animation process. The process is demonstrated using annotated examples drawn from popular fiction text that are converted into animation sequences, confirming that the desired results can be achieved with only highlevel human direction.

Infrared face recognition: a literature review

Automatic face recognition (AFR) is an area with immense practical potential which includes a wide range of commercial and law enforcement applications, and it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in AFR continues to improve, benefiting from advances in a range of different fields including image processing, pattern recognition, computer graphics and physiology. However, systems based on visible spectrum images continue to face challenges in the presence of illumination, pose and expression changes, as well as facial disguises, all of which can significantly decrease their accuracy. Amongst various approaches which have been proposed in an attempt to overcome these limitations, the use of infrared (IR) imaging has emerged as a particularly promising research direction. This paper presents a comprehensive and timely review of the literature on this subject.

Pedestrian steering behaviour modelling within the built environment

Prediction of pedestrians’ steering behaviours within the built environments under normal and non-panic situations is useful for a wide range of applications, which include social science, psychology, architecture, and computer graphics. The main focus is on prediction of the pedestrian walking paths and the influences from the surrounding environment from the engineering point of view.

Motion Bank : Phase One

 Motion Bank Phase One (2010-2013) was a four-year international and interdisciplinary research project of The Forsythe Company providing a broad context for research into choreographic practice. The main focus was on the creation of on-line digital scores in collaboration with guest choreographers, to be made publicly available via this website. For Phase One, the guest choreographers were Deborah Hay, Jonathan Burrows & Matteo Fargion, Bebe Miller and Thomas Hauert. Teams from the Motion Bank Score Partners worked with these artists to make their diverse choreographic approaches accessible in new ways through the digital medium with the results published here: http://scores.motionbank.org/. Alongside this core research, Motion Bank Education Partners and an International Education Workgroup researched ways to integrate the new on-line digital scores and related choreographic resources produced by other artists into their academic programs. Accompanying the Motion Bank education research was an interdisciplinary initiative titled Dance Engaging Science aiming to stimulate new forms of collaborative research involving dance practice. Motion Bank public events offered at The Frankfurt Lab included performances and talks with the guest choreographers as well as a series of Motion Bank Workshops with internationally recognized practitioners from different fields. An extensive series of reports and documentation on all Motion Bank activities and results are available on-line at http://motionbank.org.

Motion Bank Score Partners:
- Advanced Computing Center for the Arts and Design and Department of Dance at The Ohio State University
- Fraunhofer Institute for Computer Graphics Research IGD
- Hochschule Darmstadt - University of applied sciences
- Hochschule für Gestaltung (HFG) Offenbach.

Motion Bank Education Partners:
- Frankfurt University of Music and Performing Arts
- Palucca Hochschule für Tanz Dresden

Infrared face recognition: a comprehensive review of methodologies and databases

Automatic face recognition is an area with immense practical potential which includes a wide range of commercial and law enforcement applications. Hence it is unsurprising that it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in face recognition continues to improve, benefitting from advances in a range of different research fields such as image processing, pattern recognition, computer graphics, and physiology. Systems based on visible spectrum images, the most researched face recognition modality, have reached a significant level of maturity with some practical success. However, they continue to face challenges in the presence of illumination, pose and expression changes, as well as facial disguises, all of which can significantly decrease recognition accuracy. Amongst various approaches which have been proposed in an attempt to overcome these limitations, the use of infrared (IR) imaging has emerged as a particularly promising research direction. This paper presents a comprehensive and timely review of the literature on this subject. Our key contributions are (i) a summary of the inherent properties of infrared imaging which makes this modality promising in the context of face recognition; (ii) a systematic review of the most influential approaches, with a focus on emerging common trends as well as key differences between alternative methodologies; (iii) a description of the main databases of infrared facial images available to the researcher; and lastly (iv) a discussion of the most promising avenues for future research. © 2014 Elsevier Ltd.

Biologically inspired vector fields to generate hair directions

This paper describes how biologically inspired vector fields can be used to partially automate the manual and time-consuming process of specifying hair directions. This approach replicates the consequence of stretching of skin from natural hair development process, in contrast to replicating the appearance of hair. The direction of each hair on the surface of an arbitrary 3D model is determined by interpolating the solution vector field that satisfies a set of user-defined constraints describing the stretching of skin. Results found that the generated hair directional pattern closely resembles that found naturally. Further investigation revealed that the presence of naturally occurring hair types and the varying distribution of hair directions induced by the calculated vector field enhanced the realism of hair coats generated using this approach. Aside from hair or fur, this approach can also be applied to hair-like masses such as grass, feathers, or scales.

Using Amos graphics to enhance the understanding and communication of multiple regression

Support for the saying “a picture is worth a 1000 words’ has been consistently found within statistics education. Graphical images are effective in promoting understanding and communication of statistical concepts and results to a variety of audiences. The computer software package, AMOS, was developed for the analysis of structural equation models (SEM) and has a user-friendly graphical interface. However, courses in SEM are generally found only at the postgraduate level. This paper argues that the graphical interface of AMOS has the potential to enhance conceptual understanding and communication of results in undergraduate statistical courses. More specifically, approaches to the teaching and communication of results of multiple regression models when using SPSS and AMOS will be examined and compared.