Aline Normoyle

Automatic construction of a minimum size motion graph

Motion capture data have been used effectively in many areas of human motion synthesis. Among those, motion graph-based approaches have shown great promise for novice users due to their ability to generate long motions and the fully automatic process of motion synthesis. The performance of motion graph based approaches, however, relies heavily on selecting a good set of motions used to build the graph. This motion set needs to contain enough motions to achieve good connectivity and smooth transitions. At the same time, the motion set needs to be small for fast motion synthesis. Manually selecting a good motion set that achieves these requirements is difficult, especially given that motion capture databases are growing larger to provide a richer variety of human motions. Therefore we propose an automatic approach to select a good motion set. We cast the motion selection problem as a search for a minimum size subgraph from a large motion graph representing the motion capture database and propose an efficient algorithm, called the Iterative Sub-graph Algorithm, to find a good approximation to the optimal solution. Our approach especially benefits novice users who desire simple and fully automatic motion synthesis tools, such as motion graph-based techniques.

Evaluating perceived trust from procedurally animated gaze

Adventure role playing games (RPGs) provide players with increasingly expansive worlds, compelling storylines, and meaningful fictional character interactions. Despite the fast-growing richness of these worlds, the majority of interactions between the player and non-player characters (NPCs) still remain scripted. In this paper we propose using an NPCs animations to reflect how they feel towards the player and as a proof of concept, investigate the potential for a straightforward gaze model to convey trust. Through two perceptual experiments, we find that viewers can distinguish between high and low trust animations, that viewers associate the gaze differences specifically with trust and not with an unrelated attitude (aggression), and that the effect can hold for different facial expressions and scene contexts, even when viewed by participants for a short (five second) clip length. With an additional experiment, we explore the extent that trust is uniquely conveyed over other attitudes associated with gaze, such as interest, unfriendliness, and admiration.

The effect of posture and dynamics on the perception of emotion

Motion capture remains a popular and widely-used method for animating virtual characters. However, all practical applications of motion capture rely on motion editing techniques to increase the reusability and flexibility of captured motions. Because humans are proficient in detecting and interpreting subtle details in human motion, understanding the perceptual consequences of motion editing is essential. Thus in this work, we perform three experiments to gain a better understanding of how motion editing might affect the emotional content of a captured performance, particularly changes in posture and dynamics, two factors shown to be important perceptual indicators of bodily emotions. In these studies, we analyse the properties (angles and velocities) and perception (recognition rates and perceived intensities) of a varied set of full-body motion clips representing the six emotions anger, disgust, fear, happiness, sadness, and surprise. We have found that emotions are mostly conveyed through the upper body, that the perceived intensity of an emotion can be reduced by blending with a neutral motion, and that posture changes can alter the perceived emotion but subtle changes in dynamics only alter the intensity.

Stochastic activity authoring with direct user control

Crowd activities are often randomized to create the appearance of heterogeneity. However, the parameters that control randomization are frequently hard to tune because it is unclear how changes at the character level affect the high-level appearance of the crowd. We propose a method for computing randomization parameters that supports direct animator control. Given details about the environment, available activities, timing information and the desired high-level appearance of the crowd, we model the problem as a graph, formulate a convex optimization problem, and solve for a set of stochastic transition rates which satisfy the constraints. Unlike the use of heuristics for adding randomness to crowd activities, our approach provides guarantees on convergence to the desired result, allows for decentralized simulation, and supports a variety of constraints. In addition, because the rates can be pre-computed, no additional runtime processing is needed during simulation.

An embeddable testbed for insurgent and terrorist agent theories: InsurgiSim

Many simulators today contain traditional opponents and lack an asymmetric insurgent style adversary. InsurgiSim prototypes an embeddable testbed containing a threat network of agents that one can easily configure and deploy for training and analysis purposes. The insurgent network was constructed inside a socio-cognitive agent framework (FactionSim-PMFserv) that includes: (a) a synthesis of best-of-breed models of personality, culture, values, emotions, stress, social relations, mobilization, as well as (b) an IDE for authoring and managing reusable archetypes and their task-sets (Section 2). Agents and markups in this library are not scripted, and act to follow their values and fulfill their needs. So its desirable to profile the agents (eg, faction leaders, cell logisticians, followers, bomb maker, financier, recruiter, etc.) as faithfully to the real world as possible. Doing this will improve the utility of InsurgiSim for studying what may be driving the insurgent agents in a given area of operation as Section 3 explains. InsurgiSims bridge is an HLA federate and can be embedded to drive all or some of the insurgent agents in a 3rd party simulator. Three such examples are summarized in Section 4. The paper closes with next steps to improve InsurgiSims capabilities and utility.

Transgression and atonement

This paper presents an approach to modeling social transgressions in agent based systems. The approach is intended to be abstract enough that it may be used with many different theories of transgression, apology, forgiveness, etc. In the first half of the paper, we consider what features of transgressions, peoples emotional reactions to transgressions, and forgiveness are important, primarily by surveying social sciences literature. In the second half, we discuss an implementation of our approach in PMFserv, an agent based socio-cognitive modeling framework.

How do stylistic motions differ numerically from neutral ones

Viewers effortlessly decouple action from style for human motion. Regardless of whether style refers to the subtle differences between individuals (John Waynes walk versus Charlie Chaplins walk) or to the manner in which the same action is expressed (such as a sad walk versus a nervous walk), the core intent of an action is readily recognizable.