Autonomous Secondary Gaze Behaviours

In this paper we describe secondary behaviour, this is behaviour that is generated autonomously for an avatar. The user will control various aspects of the avatars behaviour but a truly expressive avatar must produce more complex behaviour than a user could specify in real time. Secondary behaviour provides some of this expressive behaviour autonomously. However, though it is produced autonomously it must produce behaviour that is appropriate to the actions that the user is controlling (the primary behaviour) and it must produce behaviour that corresponds to what the user wants. We describe an architecture which achieves these to aims by tagging the primary behaviour with messages to be sent to the secondary behaviour and by allowing the user to design various aspects of the secondary behaviour before starting to use the avatar. We have implemented this general architecture in a system which adds gaze behaviour to user designed actions

Integrating internal behavioural models with external expression

Users will believe in a virtual character more if they can empathise with it and understand what ‘makes it tick’. This will be helped by making the motivations of the character, and other processes that go towards creating its behaviour, clear to the user. This paper proposes that this can be achieved by linking the behavioural or cognitive system of the character to expressive behaviour. This idea is discussed in general and then demonstrated with an implementation that links a simulation of perception to the animation of a character’s eyes

Artificial intelligence: ChatGPT and human gullibility

Artificial intelligence (AI) has advanced rapidly in the past decade. The arrival of ChatGPT last year has pushed the debate about AI into the public sphere. ChatGPT, and similar tools, do things we once thought were outside the ability of computers. This raises questions for how we educate people about the capability and the limitations of such tools. This article provides an overview of artificial intelligence and explores what ChatGPT is capable of doing. It also raises questions about morality, responsibility, sentience, intelligence, and how humans’ propensity to anthropomorphise makes us gullible and thus ready to believe that this technology is delivering something that it cannot

Quantitative Analysis of Saliency Models

Previous saliency detection research required the reader to evaluate performance qualitatively, based on renderings of saliency maps on a few shapes. This qualitative approach meant it was unclear which saliency models were better, or how well they compared to human perception. This paper provides a quantitative evaluation framework that addresses this issue. In the first quantitative analysis of 3D computational saliency models, we evaluate four computational saliency models and two baseline models against ground-truth saliency collected in previous work.Comment: 10 page

Image Sampling with Quasicrystals

We investigate the use of quasicrystals in image sampling. Quasicrystals produce space-filling, non-periodic point sets that are uniformly discrete and relatively dense, thereby ensuring the sample sites are evenly spread out throughout the sampled image. Their self-similar structure can be attractive for creating sampling patterns endowed with a decorative symmetry. We present a brief general overview of the algebraic theory of cut-and-project quasicrystals based on the geometry of the golden ratio. To assess the practical utility of quasicrystal sampling, we evaluate the visual effects of a variety of non-adaptive image sampling strategies on photorealistic image reconstruction and non-photorealistic image rendering used in multiresolution image representations. For computer visualization of point sets used in image sampling, we introduce a mosaic rendering technique.Comment: For a full resolution version of this paper, along with supplementary materials, please visit at http://www.Eyemaginary.com/Portfolio/Publications.htm

Creases and boundary conditions for subdivision curves

AbstractOur goal is to find subdivision rules at creases in arbitrary degree subdivision for piece-wise polynomial curves, but without introducing new control points e.g. by knot insertion. Crease rules are well understood for low degree (cubic and lower) curves. We compare three main approaches: knot insertion, ghost points, and modifying subdivision rules. While knot insertion and ghost points work for arbitrary degrees for B-splines, these methods introduce unnecessary (ghost) control points.The situation is not so simple in modifying subdivision rules. Based on subdivision and subspace selection matrices, a novel approach to finding boundary and sharp subdivision rules that generalises to any degree is presented. Our approach leads to new higher-degree polynomial subdivision schemes with crease control without introducing new control points

Semi-Autonomous Avatars: A New Direction for Expressive User Embodiment

Computer animated characters are rapidly becoming a regular part of our lives. They are starting to take the place of actors in films and television and are now an integral part of most computer games. Perhaps most interestingly in on-line games and chat rooms they are representing the user visually in the form of avatars, becoming our on-line identities, our embodiments in a virtual world. Currently online environments such as “Second Life” are being taken up by people who would not traditionally have considered playing games before, largely due to a greater emphasis on social interaction. These environments require avatars that are more expressive and that can make on-line social interactions seem more like face-to-face conversations. Computer animated characters come in many different forms. Film characters require a substantial amount of off-line animator effort to achieve high levels of quality; these techniques are not suitable for real time applications and are not the focus of this chapter. Non-player characters (typically the bad guys) in games use limited artificial intelligence to react autonomously to events in real time. However avatars are completely controlled by their users, reacting to events solely through user commands. This chapter will discuss the distinction between fully autonomous characters and completely controlled avatars and how the current differentiation may no longer be useful, given that avatar technology may need to include more autonomy to live up to the demands of mass appeal. We will firstly discuss the two categories and present reasons to combine them. We will then describe previous work in this area and finally present our own framework for semi-autonomous avatars