Richard Southern

Bystander Responses to a Violent Incident in an Immersive Virtual Environment

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.

A stateless client for progressive view-dependent transmission

We present a framework for real-time view-dependent refinement, and adapt it to the task of browsing large model repositories on the Internet. We introduce a novel hierarchical representation of atomic operations based on a graph structure, and provide a correspondence between the nodes of this hierarchy and a spatial representation of these operations, called visibility spheres. Selective refinement is achieved by performing a breadth first search on the graph. We show that the graph representation allows for significant space savings. The framework presented makes options available for performance tailoring. By efficient traversal of the graph structure an ordered list of refinements can be generated which are progressive and evenly distributed over the refinement area. This list can easily be truncated to comply with polygon limitations indicated by a client. CR Categories: I.3.2 [Computer Graphics]: Picture/Image Generation—Display Algorithms; I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling—Surfaces and Object Representations

Creation and Control of Real-time Continuous Level of Detail on Programmable Graphics Hardware

Continuity in level of detail sequences is essential in hiding visual artefacts that occur when switching between discrete levels of detail. However, construction and implementation of these sequences is prohibitively complex. We present a new structure, the g‐mesh, which greatly simplifies the implementation of continuous level of detail in large scenes. We also introduce a novel greedy predictive level of detail control system suited to the g‐mesh. Finally we achieve a dramatic improvement in the rendering of morphing sequences by exploiting current graphics hardware.

Blue noise sampling using an SPH-based method

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 Lloyds 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.

Adaptive motion synthesis for virtual characters: a survey

Character motion synthesis is the process of artificially generating natural motion for a virtual character. In film, motion synthesis can be used to generate difficult or dangerous stunts without putting performers at risk. In computer games and virtual reality, motion synthesis enriches the player or participant experience by allowing for unscripted and emergent character behavior. In each of these applications the ability to adapt to changes to environmental conditions or to the character in a smooth and natural manner, while still conforming with user-specified constraints, determines the utility of a method to animators and industry practitioners. This focus on adaptation capability distinguishes our survey from other reviews which focus on general technology developments. Three main methodologies (example-based; simulation-based and hybrid) are summarised and evaluated using compound metrics: adaptivity, naturalness and controllability. By assessing existing techniques according to this classification we are able to determine how well a method corresponds to users’ expectations. We discuss optimization strategies commonly used in motion synthesis literature, and also contemporary perspectives from biology which give us a deeper insight into this problem. We also present observations and reflections from industry practitioners to reveal the operational constraints of character motion synthesis techniques. Our discussion and review presents a unique insight into the subject, and provide essential guidance when selecting appropriate methods to design an adaptive motion controller.

Generic memoryless polygonal simplification

We present a new framework for generic and adaptive memoryless surface simplification. We show that many existing techniques of simplification based on the edge collapse / vertex split operations differ only in terms of memory-resident data used to improve running performance. By removing the need for this memory we are able to implement multiple simplification techniques on the same platform. Our generic platform can be used as a tool for the generation and evaluation of custom error metrics. We present two new error metrics designed using our generic framework. We present a novel batched ordering technique based on the generic simplification framework, which allows for adaptive simplification and automatic level-of-detail generation.

Motion Adaptation With Motor Invariant Theory

Bipedal walking is not fully understood. Motion generated from methods employed in robotics literature is stiff and is not nearly as energy efficient as what we observe in nature. In this paper, we propose validity conditions for motion adaptation from biological principles in terms of the topology of the dynamic system. This allows us to provide a closed-form solution to the problem of motion adaptation to environmental perturbations. We define both global and local controllers that improve structural and state stability, respectively. Global control is achieved by coupling the dynamic system with a neural oscillator, which preserves the periodic structure of the motion primitive and ensures stability by entrainment. A group action derived from Lie group symmetry is introduced as a local control that transforms the underlying state space while preserving certain motor invariants. We verify our method by evaluating the stability and energy consumption of a synthetic passive dynamic walker and compare this with motion data of a real walker. We also demonstrate that our method can be applied to a variety of systems.

Motion-Sensitive Anchor Identification of Least-Squares Meshes from Examples

A least-squares mesh is a surface representation consisting of a small set of anchor points and the differential and topological properties of the surface. In this paper, we present a novel method to identify motion-sensitive anchor points for least-squares meshes from a set of examples. We present a new method, called clustered teleconnection analysis, to identify the maximally excited points in a subset of basis vectors deduced using principal component analysis. We demonstrate by means of examples that our approach has a smaller reconstruction error and equivalent performance to the current best approaches.

Automatic cage construction for retargeted muscle fitting

The animation of realistic characters necessitates the construction of complicated anatomical structures such as muscles, which allow subtle shape variation of the character’s outer surface to be displayed believably. Unfortunately, despite numerous efforts, the modelling of muscle structures is still left for an animator who has to painstakingly build up piece by piece, making it a very tedious process. What is even more frustrating is the animator has to build the same muscle structure for every new character. We propose a muscle retargeting technique to help an animator to automatically construct a muscle structure by reusing an already built and tested model (the template model). Our method defines a spatial transfer between the template model and a new model based on the skin surface and the rigging structure. To ensure that the retargeted muscle is tightly packed inside a new character, we define a novel spatial optimization based on spherical parameterization. Our method requires no manual input, meaning that an animator does not require anatomical knowledge to create realistic accurate musculature models.

Adaptive Physics---Inspired Facial Animation

In this paper, we present a new approach for facial animation. We develop a mathematical model from the physical properties of skin deformation which incorporates the action of externally applied forces and the material properties of the skins surface. A finite difference mesh which uses this model is generated automatically using a harmonic parametrization and interpolating nodes on the original surface. We determine the forces at these nodes of various face poses. By blending these forces at we can generate new intermediate shapes. In the interests of computational efficiency, we present a novel adaptive finite difference method which limits the calculation of surface constants to regions where significant deformation occurs.