The aim of this study was to investigate the effect of non-player character (NPC) appearance in games - specifically, how a character's appearance affects a player's performance, and their perception of the game. We ran an experiment where participants played a mobile game on a 9.7" tablet, the goal of which was to kill all of the enemy characters in the game. The visual appearance of the enemy characters varied in the level of aggression in appearance. One crowd had small, green characters with no weapons and minimal armour. The other crowd had red characters that were large and wearing both weapons and armour. Both crowds had the same level of aggression in behaviour, stance and animations, as well as the same intersection-test capsule to ensure the gameplay was balanced and both crowds were equally difficult to kill. As expected, the second crowd was perceived as highly aggressive and less friendly than the first crowd. We found no differences in the enjoyment levels of the game but interestingly, we found that the visual appearance of the crowd had a direct effect on the player performance in combat. In contrast to our hypothesis, players performed worse (i.e., were killed more often) when in combat against the characters with the less-aggressive appearance.

Abstract While walking through a crowd, a pedestrian experiences a large number of interactions with his neighbors. The nature of these interactions is varied, and it has been observed that macroscopic phenomena emerge from the combination of these local interactions. Crowd models have hitherto considered collision avoidance as the unique type of interactions between individuals, few have considered walking in groups. By contrast, our paper focuses on interactions due to the following behaviors of pedestrians. Following is frequently observed when people walk in corridors or when they queue. Typical macroscopic stop‐and‐go waves emerge under such traffic conditions. Our contributions are, first, an experimental study on following behaviors, second, a numerical model for simulating such interactions, and third, its calibration, evaluation and applications. Through an experimental approach, we elaborate and calibrate a model from microscopic analysis of real kinematics data collected during experiments. We carefully evaluate our model both at the microscopic and the macroscopic levels. We also demonstrate our approach on applications where following interactions are prominent.

Simulating the local behavior of small pedestrian groups among a crowd is an emerging problem. Small groups are commonly found in general crowds and their behavior are significantly distinguished from that of individual pedestrians. In this paper, we propose a novel approach to simulate the walking behavior of such small groups. We construct dynamic group formations which not only facilitate easy communication between members within the same group but also adapt to the environment constraint. Moreover, an extended collision avoidance algorithm based on Optimal Reciprocal Collision Avoidance (ORCA) is proposed taking into account the factors of group cohesion and reaction flexibility so as to generate diverse interaction behavior between walkers. Several examples demonstrate the efficiency of the proposed algorithm.

Modeling believable autonomous agents needs to take into account many different aspects from very different disciplines, ranging from cognitive psychology to mechanics. In this paper, we focus on research work dedicated to the modeling of human decision in a reactive way, a domain in-between the biomechanical motion control of the activity and the rational and social background which motivates and shapes the execution of such activities. We cover models of reactive human behaviors introduced in computer science and cognitive science, assessing and comparing them from the application-oriented perspective of modeling credible real-time virtual anthropomorphic actors. Copyright © 2010 John Wiley & Sons, Ltd.

ABSTRACT The seamless integration of virtual characters into dynamic scenes captured by video is a challenging problem. In order to achieve consistent composite results, both the virtual and real characters must share the same geometrical constraints and their interactions must follow some common sense. One essential question is how to detect the motion of real objects—such as real characters moving in the video—and how to steer virtual characters accordingly to avoid unrealistic collisions. We propose an online solution. First, by analysis of the input video, the motion states of the real pedestrians are recovered into a common world 3D coordinate system. Meanwhile, a simplified accuracy measurement is defined to represent the confidence of the motion estimate. Then, under the constraints imposed by the real dynamic objects, the motion of virtual characters are accommodated by a uniform steering model. The final step is to merge virtual objects back to the real video scene by taking into account visibility and occlusion constraints between real foreground objects and virtual ones. Several examples demonstrate the efficiency of the proposed algorithm. Copyright © 2011 John Wiley & Sons, Ltd.

This volume of Computer Animation and Virtual Worlds (CAVW) contains a selection of papers submitted to CASA 2010, the 23rd International Conference on Computer Animation and Social Agents. CASA is one of the premier international conferences in the field of computer animation and social agents, organized under the auspices of the Computer Graphics Society (CGS). It has been founded in 1988, and, over the last years, it has been organized in Europe: Geneva (2002, 2004, 2006), Hasselt (2007), Amsterdam (2009); in USA: Philadelphia (1998, 2000), New Jersey (2003); and in Asia: Seoul (2001, 2008), Hong Kong (2005). This year, CASA 2010 was organized in Saint-Malo, France from the 30th of May to the 2nd of June 2010. The organization was done by Bunraku, an INRIA Project-team in common with CNRS, INSA of Rennes, University of Rennes 1, and Ecole Normale Supérieure de Cachan. The CASA 2010 edition received 104 submissions from 27 countries and 6 continents. Each submission received at least 3 reviews and 32 among them were selected to appear in this special issue of Computer Animation and Virtual Worlds. We thank all the authors who have submitted their work to this conference allowing us to present this nice and diversified program. We thank also the International Program Committee members and the additional external reviewers for the time and energy they have invested in the reviewing process. A particular thank goes to the INRIA conference support team, especially to Edith Blin-Guyot and Steeve Tessier, for their support in organizing the conference, taking care of financial, material, and organizational matters. CASA 2010 has been sponsored by INRIA, by the IRIS European Network of Excellence (Integrating Research in Interactive Storytelling), by GDR IG (Groupement de Recherche Informatique Graphique), by Fondation Michel Métivier, by the Brittany Regional Council, by the University of Rennes 1, by the Ecole Normale Supérieure de Cachan, and by the Biometrics Company. The 32 papers presented in this special issue are divided into several categories: Cartoon and Sketch-based animation techniques, Stylized animation, Deformable models, Meshes, Physically based animation, Motion Analysis and Synthesis, Steering and Crowds, Facial expression, Social Agents, and finally Augmented Reality.

In the everyday exercise of controlling their locomotion, humans rely on their optic flow of the perceived environment to achieve collision-free navigation. In crowds, in spite of the complexity of the environment made of numerous obstacles, humans demonstrate remarkable capacities in avoiding collisions. Cognitive science work on human locomotion states that relatively succinct information is extracted from the optic flow to achieve safe locomotion. In this paper, we explore a novel vision-based approach of collision avoidance between walkers that fits the requirements of interactive crowd simulation. By simulating humans based on cognitive science results, we detect future collisions as well as the level of danger from visual stimuli. The motor-response is twofold: a reorientation strategy prevents future collision, whereas a deceleration strategy prevents imminent collisions. Several examples of our simulation results show that the emergence of self-organized patterns of walkers is reinforced using our approach. The emergent phenomena are visually appealing. More importantly, they improve the overall efficiency of the walkers' traffic and avoid improbable locking situations.

Abstract This paper addresses the problem of virtual pedestrian autonomous navigation for crowd simulation. It describes a method for solving interactions between pedestrians and avoiding inter‐collisions. Our approach is agent‐based and predictive: each agent perceives surrounding agents and extrapolates their trajectory in order to react to potential collisions. We aim at obtaining realistic results, thus the proposed model is calibrated from experimental motion capture data. Our method is shown to be valid and solves major drawbacks compared to previous approaches such as oscillations due to a lack of anticipation. We first describe the mathematical representation used in our model, we then detail its implementation, and finally, its calibration and validation from real data.

Abstract Autonomous agents cannot exist in an environment without interacting with the world surrounding them. In this paper we propose an informed environment based on synoptic objects which contain a synopsis of the interactions they can undergo. Through the use of interactive surfaces (ISs) we manage to describe the surfaces of interest on the object itself and the space affected by the object during interaction. Then, by defining a set of seven basic actions, the objects can describe the interaction process through these actions to any agent implementing them. The description of the interaction process is done through complex actions which indicate the order in which the basic actions need to be accomplished and what to do depending on the result of the undertaken action. Copyright © 2007 John Wiley & Sons, Ltd.

This paper investigates the use of camera motions, in order to improve the sensation of walking in a Virtual Environment. A simple model of camera motion is first proposed. This model uses: (1) oscillating motions for the position of the camera, and (2) a compensation motion which changes the orientation of the camera and simulate oculomotor compensation to keep a constant focal point when walking. Then we describe two experiments which were conducted to study the characteristics of our model and the preference of the users in terms of sensation of walking. The first experiment compared the use of oscillating camera motions along the three directions of space. The oscillating motions were all preferred to the control condition (i.e. a linear motion, as if the user was driving a car). Furthermore, the participants preferred oscillating motions along the vertical axis, compared with the two other directions of space. The second experiment was focused on the use of a compensation motion. It showed that on average participants preferred a compensated motion during the walk, as compared with a motion with a constant orientation of the camera. These results are consistent with the way our body and eyes move naturally when walking in real life. Taken together, our results suggest that camera motions can considerably improve the sensation of walking in virtual environments. Camera motions could be further introduced in numerous applications of virtual reality in which the simulation of walking is important, such as: architectural visits, training simulations, or videogames.

Abstract This paper treats two linked subjects underlying behavioural simulation. First, the way to describe a virtual environment through an informed hierarchical abstract graph. This graph stores some pre‐computations such as potential visibility sets, oriented grids, or densities of people, which can be used individually by simulated entities. Second, the way to use this abstract graph to perform a realistic and efficient path planning, which takes care of individual preferences as well as individual knowledge of the environment. Moreover, the path planning method we propose is reactive to some events, reflecting the perceived modifications of the environment, which allows the entity to adapt its behaviour in consequence. Copyright © 2006 John Wiley & Sons, Ltd.

Abstract The navigation activity is an every day practice for any human being capable of locomotion. Our objective in this work is to reproduce this crucial human activity inside virtual environments. Putting together the high complexity of a realistic environment such as a city, a big amount of virtual humans and the real‐time constraint requires to optimize each aspect of the animation process. In this paper, we present a suitable topological structuring of the geometric environment to allow fast path finding as well as an efficient reactive navigation algorithm for virtual humans evolving inside a crowd.

Abstract Behavioural models offer the ability to simulate autonomous agents like organisms and living beings. Psychological studies have shown that human behaviour can be described by a perception–decision–action loop, in which the decisional process should integrate several programming paradigms such as real time, concurrency and hierarchy. Building such systems for interactive simulation requires the design of a reactive system treating flows of data to and from the environment, and involving task control and preemption. Since a complete mental model based on vision and image processing cannot be constructed in real time using purely geometrical information, higher levels of information are needed in a model of the virtual environment. For example, the autonomous actors of a virtual world would exploit the knowledge of the environment topology to navigate through it. Accordingly, in this paper we present our programming environment for real‐time behavioural animation which is compounded of a general animation and simulation platform, a behavioural modelling language and a scenario‐authoring tool. Those tools has been used for different applications such as pedestrian and car driver interaction in urban environments, or a virtual museum populated by a group of visitors. Copyright © 2002 John Wiley & Sons, Ltd.

In order to populate virtual cities, it is necessary to specify the behaviour of dynamic entities such as pedestrians or car drivers. Since it is not possible to construct in real time a complete mental model only from vision and image processing, we have to add higher levels of information than the geometrical one in the model of the virtual environment. In this article, a pedestrian behavioural model which exploits the information produced by VUEMS, our city modeller, is presented.

In order to populate virtual cities, it is necessary to specify the behaviour of dynamic entities such as pedestrians or car drivers. Since a complete mental model based on vision and image processing cannot be constructed in real time using purely geometrical information, higher levels of information are needed in a model of the virtual environment. For example, the autonomous actors of a virtual world would exploit the knowledge of the environment topology to navigate through it. In this article, we present a model of virtual urban environments using structures and information suitable for behavioural animations. Thanks to this knowledge, autonomous virtual actors can behave like pedestrians or car drivers in a complex city environment. A city modeler has been designed, using this model of urban environment, and enables complex urban environments for behavioural animation to be automatically produced.

We present a generic animation and simulation platform which integrates the different animation models: descriptive, generative and behavioural models. The integration of these models in the same platform offers to each dynamic entity a more realistic and a richer environment, and thereby increases possible interactions between an actor and its environment. Therefore we describe the kernel of the platform, then we explain how it is used from the programmer's point of view and we illustrate its use in the field of driving simulation.

The Praxitele project is responsible for the design of a new kind of transportation in an urban environment, which consists of a fleet of electric public cars. These public cars are capable of autonomous motion on given journeys between stations. The realization of such a project requires experimentations with the behaviour of autonomous vehicles in the urban environment. Because of the danger connected with these kinds of experiments in a real site, it,vas necessary to design a virtual urban environment in which simulations could be done. Reproducing the real traffic of a city, as completely as possible, implies the simulation of autonomous entities like living beings. Such entities are able to perceive their environment, to communicate with other creatures and to execute some actions either on themselves or on their environment. Databases for virtual environments are often confined to the geometric level, when they must also contain physical, topological and semantic information. Accordingly in this paper we present VUEMS, a Virtual Urban Environment Modelling System which is designed to manage different levels of representation by assembling geometric, topological and semantic data in the field of traffic simulation. From real world data (when available), we construct a Model of the Virtual Urban Environment, integrating all the information needed to describe the realistic behaviour of car drivers.

The Praxitele project is responsible for the design of a new kind of transportation in an urban environment, which consists of a fleet of electric public cars. The realization of such a project requires experimentations with the behaviour of autonomous vehicles in the urban environment. It was necessary to design a virtual urban environment in which simulations could be done. Reproducing the real traffic of a city as completely as possible, implies the simulation of autonomous entities like living beings. Such entities are able to perceive their environment, to communicate with other creatures and to execute some actions either on themselves or on their environment. Interactions between an object and its environment are, most of the time, very simple: sensors and actuators are reduced to minimal capabilities which permit them only to avoid obstacles in a 2D or 3D world. This is due to the fact that databases for virtual environments are often confined to the geometric level, when they must also contain physical, topological and semantic information. Accordingly, we propose a model which is designed to connect different levels of representation, by assembling geometric, topological and semantic data in the field of traffic simulation, and its implementation in VUEMS, a Modelling System of Urban Road Network. From real world data (when available), we construct a model of the virtual urban environment, integrating all the information needed to describe the realistic behaviour of car drivers and pedestrians.

Abstract In this paper, we present a dynamic model associated with an intelligent CAD system aiming at the modeling of an architectural scene sketch. Our design methodology has been developed to simulate the process of a user who tries to give a description of a scene from a set of mental images. The scene creation is based on a script which describes the environment from the point of view of an observer who moves across the scene. The system is based on a declarative method viewed as a stepwise refinement process. For the scene representation, a qualitative model is used to describe the objects in terms of attributes, functions, methods and components. The links between objects and their components are expressed by a hierarchical structure, and a description of spatial configurations is given by using locative relations. The set of solutions consistent with the description is usually infinite. So, either one scene consistent with this description is calculated and visualized, or reasons of inconsistency are notified to the user. The resolution process consists of two steps: firstly a logical inference checks the consistency of the topological description, and secondly an optimization algorithm deals with the global description and provides a solution. Two examples illustrate our design methodology and the calculation of a scene model.