1,322 research outputs found
A survey of real-time crowd rendering
In this survey we review, classify and compare existing approaches for real-time crowd rendering. We first overview character animation techniques, as they are highly tied to crowd rendering performance, and then we analyze the state of the art in crowd rendering. We discuss different representations for level-of-detail (LoD) rendering of animated characters, including polygon-based, point-based, and image-based techniques, and review different criteria for runtime LoD selection. Besides LoD approaches, we review classic acceleration schemes, such as frustum culling and occlusion culling, and describe how they can be adapted to handle crowds of animated characters. We also discuss specific acceleration techniques for crowd rendering, such as primitive pseudo-instancing, palette skinning, and dynamic key-pose caching, which benefit from current graphics hardware. We also address other factors affecting performance and realism of crowds such as lighting, shadowing, clothing and variability. Finally we provide an exhaustive comparison of the most relevant approaches in the field.Peer ReviewedPostprint (author's final draft
Parallelized Egocentric Fields for Autonomous Navigation
In this paper, we propose a general framework for local path-planning and steering that can be easily extended to perform high-level behaviors. Our framework is based on the concept of affordances: the possible ways an agent can interact with its environment. Each agent perceives the environment through a set of vector and scalar fields that are represented in the agent’s local space. This egocentric property allows us to efficiently compute a local space-time plan and has better parallel scalability than a global fields approach. We then use these perception fields to compute a fitness measure for every possible action, defined as an affordance field. The action that has the optimal value in the affordance field is the agent’s steering decision. We propose an extension to a linear space-time prediction model for dynamic collision avoidance and present our parallelization results on multicore systems. We analyze and evaluate our framework using a comprehensive suite of test cases provided in SteerBench and demonstrate autonomous virtual pedestrians that perform steering and path planning in unknown environments along with the emergence of high-level responses to never seen before situations
Virtual humans: thirty years of research, what next?
In this paper, we present research results and future challenges in creating realistic and believable Virtual Humans. To realize these modeling goals, real-time realistic representation is essential, but we also need interactive and perceptive Virtual Humans to populate the Virtual Worlds. Three levels of modeling should be considered to create these believable Virtual Humans: 1) realistic appearance modeling, 2) realistic, smooth and flexible motion modeling, and 3) realistic high-level behaviors modeling. At first, the issues of creating virtual humans with better skeleton and realistic deformable bodies are illustrated. To give a level of believable behavior, challenges are laid on generating on the fly flexible motion and complex behaviours of Virtual Humans inside their environments using a realistic perception of the environment. Interactivity and group behaviours are also important parameters to create believable Virtual Humans which have challenges in creating believable relationship between real and virtual humans based on emotion and personality, and simulating realistic and believable behaviors of groups and crowds. Finally, issues in generating realistic virtual clothed and haired people are presente
Virtual Reality Games for Motor Rehabilitation
This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion
Example Based Caricature Synthesis
The likeness of a caricature to the original face image is an essential and often overlooked part of caricature
production. In this paper we present an example based caricature synthesis technique, consisting of shape
exaggeration, relationship exaggeration, and optimization for likeness. Rather than relying on a large training set
of caricature face pairs, our shape exaggeration step is based on only one or a small number of examples of facial
features. The relationship exaggeration step introduces two definitions which facilitate global facial feature
synthesis. The first is the T-Shape rule, which describes the relative relationship between the facial elements in an
intuitive manner. The second is the so called proportions, which characterizes the facial features in a proportion
form. Finally we introduce a similarity metric as the likeness metric based on the Modified Hausdorff Distance
(MHD) which allows us to optimize the configuration of facial elements, maximizing likeness while satisfying a
number of constraints. The effectiveness of our algorithm is demonstrated with experimental results
Real Time Animation of Virtual Humans: A Trade-off Between Naturalness and Control
Virtual humans are employed in many interactive applications using 3D virtual environments, including (serious) games. The motion of such virtual humans should look realistic (or ‘natural’) and allow interaction with the surroundings and other (virtual) humans. Current animation techniques differ in the trade-off they offer between motion naturalness and the control that can be exerted over the motion. We show mechanisms to parametrize, combine (on different body parts) and concatenate motions generated by different animation techniques. We discuss several aspects of motion naturalness and show how it can be evaluated. We conclude by showing the promise of combinations of different animation paradigms to enhance both naturalness and control
A RULE-BASED APPROACH TO ANIMATING MULTI-AGENT ENVIRONMENTS
This dissertation describes ESCAPE (Expert Systems in Computer Animation Production
Environments), a multi-agent animation system for building domain-oriented, rule-based
visual programming environments.
Much recent work in computer graphics has been concerned with producing
behavioural animations of artificial life-forms mainly based on algorithmic approaches.
This research indicates how, by adding an inference engine and rules that describe such
behaviour, traditional computer animation environments can be enhanced.
The comparison between using algorithmic approaches and using a rule-based
approach for representing multi-agent worlds is not based upon their respective claims
to completeness, but rather on the ease with which end users may express their
knowledge and control their animations with a minimum of technical knowledge.
An environment for the design of computer animations incorporating an expert
system approach is described. In addition to direct manipulation of objects on the
screen, the environment allows users to describe behavioural rules based upon both the
physical and non-physical attributes of objects. These rules can be interpreted to
suggest the transition from stage to stage or to automatically produce a longer
animation. The output from the system can be integrated into a commercially available
3D modelling and rendering package.
Experience indicates that a hybrid environment, mixing algorithmic and rule-based
approaches, would be very promising and offer benefits in application areas such
as creating realistic background scenes and modelling human beings or animals either
singly or in groups.
A prototype evaluation system and three different domains are described and
illustrated with preliminary animated images
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