Under what conditions will a bystander intervene to try to stop a violent attack by one person on another? It is generally believed that the greater the size of the crowd of bystanders, the less the chance that any of them will intervene. A complementary model is that social identity is critical as an explanatory variable. For example, when the bystander shares common social identity with the victim the probability of intervention is enhanced, other things being equal. However, it is generally not possible to study such hypotheses experimentally for practical and ethical reasons. Here we show that an experiment that depicts a violent incident at life-size in immersive virtual reality lends support to the social identity explanation. 40 male supporters of Arsenal Football Club in England were recruited for a two-factor between-groups experiment: the victim was either an Arsenal supporter or not (in-group/out-group), and looked towards the participant for help or not during the confrontation. The response variables were the numbers of verbal and physical interventions by the participant during the violent argument. The number of physical interventions had a significantly greater mean in the in-group condition compared to the out-group. The more that participants perceived that the Victim was looking to them for help the greater the number of interventions in the in-group but not in the out-group. These results are supported by standard statistical analysis of variance, with more detailed findings obtained by a symbolic regression procedure based on genetic programming. Verbal interventions made during their experience, and analysis of post-experiment interview data suggest that in-group members were more prone to confrontational intervention compared to the out-group who were more prone to make statements to try to diffuse the situation.

We propose a novel algorithm for blue noise sampling inspired by the Smoothed Particle Hydrodynamics (SPH) method. SPH is a well-known method in fluid simulation-it computes particle distributions to minimize the internal pressure variance. We found that this results in sample points (i.e., particles) with a high quality blue-noise spectrum. Inspired by this, we tailor the SPH method for blue noise sampling. Our method achieves fast sampling in general dimensions for both surfaces and volumes. By varying a single parameter our method can generate a variety of blue noise samples with different distribution properties, ranging from Lloyd's relaxation to Capacity Constrained Voronoi Tessellations (CCVT). Our method is fast and supports adaptive sampling and multi-class sampling. We have also performed experimental studies of the SPH kernel and its influence on the distribution properties of samples. We demonstrate with examples that our method can generate a variety of controllable blue noise sample patterns, suitable for applications such as image stippling and re-meshing.

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This paper describes the impact of display resolution and luminance on the responses of participants in a behavioral study that used a projection-based Immersive Virtual Reality System. The scenario was a virtual bar where participants witnessed a violent attack of one person on another due to an argument about support for a soccer club. The major response variable was the number of interventions made by participants. The study was between-groups with 10 participants in two groups pre-upgrade and post-upgrade, both in the same 4-screen Cave-like system. However, the post-upgrade group experienced the scenario with projectors that had a significantly higher level of resolution and luminance than those experienced by the pre-upgrade group.The results show that, other things being equal, the number of both verbal and physical interventions was greater amongst those in the post-upgrade group compared to the pre-upgrade group.

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Traditional work on bystander intervention in violent emergencies has found that the larger the group, the less the chance that any individual will intervene. Here, we tested the impact on helping behavior of the affiliation of the bystanders with respect to the participants. We recruited 40 male supporters of the U.K. Arsenal football club for a two-factor between groups study with 10 participants per group. Each participant spoke with a virtual human Arsenal supporter (V), the scenario displayed in a virtual reality system. During this conversation, another virtual character (P), not an Arsenal fan, verbally abused V for being an Arsenal fan leading eventually to physical pushing. There was a group of three virtual bystanders who were all either Arsenal supporters indicated by their shirts, or football fans wearing unbranded shirts. These bystanders either encouraged the participant to intervene or dissuaded him. We recorded the number of times that participants intervened to help V during the aggression. We found that participants were more likely to intervene when the bystanders were out-group with respect to the participant. By comparing levels of intervention with a “baseline” study (identical except for the presence of bystanders), we conclude that the presence of in-group bystanders decreases helping. We argue therefore that, other things being equal, diffusion of responsibility is more likely to be overcome when participant and victim share group membership, but bystanders do not. Our findings help to develop understanding of how diffusion of responsibility works by combining elements of both the bystander effect and the social identity approach to bystander behavior.