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

Feeling crowded yet?: Crowd simulations for VR

With advances in virtual reality technology and its multiple applications, the need for believable, immersive virtual environments is increasing. Even though current computer graphics methods allow us to develop highly realistic virtual worlds, the main element failing to enhance presence is autonomous groups of human inhabitants. A great number of crowd simulation techniques have emerged in the last decade, but critical details in the crowd's movements and appearance do not meet the standards necessary to convince VR participants that they are present in a real crowd. In this paper, we review recent advances in the creation of immersive virtual crowds and discuss areas that require further work to turn these simulations into more fully immersive and believable experiences.Peer ReviewedPostprint (author's final draft

Using image morphing for memory-efficient impostor rendering on GPU

Real-time rendering of large animated crowds consisting thousands of virtual humans is important for several applications including simulations, games and interactive walkthroughs; but cannot be performed using complex polygonal models at interactive frame rates. For that reason, several methods using large numbers of pre-computed image-based representations, which are called as impostors, have been proposed. These methods take the advantage of existing programmable graphics hardware to compensate the computational expense while maintaining the visual fidelity. Making the number of different virtual humans, which can be rendered in real-time, not restricted anymore by the required computational power but by the texture memory consumed for the variety and discretization of their animations. In this work, we proposed an alternative method that reduces the memory consumption by generating compelling intermediate textures using image-morphing techniques. In order to demonstrate the preserved perceptual quality of animations, where half of the key-frames were rendered using the proposed methodology, we have implemented the system using the graphical processing unit and obtained promising results at interactive frame rates

Generating, animating, and rendering varied individuals for real-time crowds

To simulate realistic crowds of virtual humans in real time, three main requirements need satisfaction. First of all, quantity, i.e., the ability to simulate thousands of characters. Secondly, quality, because each virtual human composing a crowd needs to look unique in its appearance and animation. Finally, efficiency is paramount, for an operation usually efficient on a single virtual human, becomes extremely costly when applied on large crowds. Developing an architecture able to manage all three aspects is a challenging problem that we have addressed in our research. Our first contribution is an efficient and versatile architecture called YaQ, able to simulate thousands of characters in real time. This platform, developed at EPFL-VRLab, results from several years of research and integrates state-of-the-art techniques at all levels: YaQ aims at providing efficient algorithms and real-time solutions for populating globally and massively large-scale empty environments. YaQ thus fits various application domains, such as video games and virtual reality. Our architecture is especially efficient in managing the large quantity of data that is used to simulate crowds. In order to simulate large crowds, many instances of a small set of human templates have to be generated. From this starting point, if no care is taken to vary each character individually, many clones appear in the crowd. We present several algorithms to make each individual unique in the crowd. Firstly, we introduce a new method to distinguish body parts of a human and apply detailed color variety and patterns to each one of them. Secondly, we present two techniques to modify the shape and profile of a virtual human: a simple and efficient method for attaching accessories to individuals, and efficient tools to scale the skeleton and mesh of an instance. Finally, we also contribute to varying individuals' animation by introducing variations to the upper body movements, thus allowing characters to make a phone call, have a hand in their pocket, or carry heavy accessories, etc. To achieve quantity in a crowd, levels of detail need to be used. We explore the most adequate solutions to simulate large crowds with levels of detail, while avoiding disturbing switches between two different representations of a virtual human. To do so, we develop solutions to make most variety techniques scalable to all levels of detail

Group emotion modelling and the use of middleware for virtual crowds in video-games

In this paper we discuss the use of crowd simulation in video-games to augment their realism. Using previous works on emotion modelling and virtual crowds we define a game world in an urban context. To achieve that, we explore a biologically inspired human emotion model, investigate the formation of groups in crowds, and examine the use of physics middleware for crowds. Furthermore, we assess the realism and computational performance of the proposed approach. Our system runs at interactive frame-rate and can generate large crowds which demonstrate complex behaviour

LCrowdV: Generating Labeled Videos for Simulation-based Crowd Behavior Learning

We present a novel procedural framework to generate an arbitrary number of labeled crowd videos (LCrowdV). The resulting crowd video datasets are used to design accurate algorithms or training models for crowded scene understanding. Our overall approach is composed of two components: a procedural simulation framework for generating crowd movements and behaviors, and a procedural rendering framework to generate different videos or images. Each video or image is automatically labeled based on the environment, number of pedestrians, density, behavior, flow, lighting conditions, viewpoint, noise, etc. Furthermore, we can increase the realism by combining synthetically-generated behaviors with real-world background videos. We demonstrate the benefits of LCrowdV over prior lableled crowd datasets by improving the accuracy of pedestrian detection and crowd behavior classification algorithms. LCrowdV would be released on the WWW

Developing serious games for cultural heritage: a state-of-the-art review

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented