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

Automated Analysis of Human Factors Requirements

Computational ergonomic analyses are often laboriously tested one task at a time. As digital human models improve, we can partially automate the entire analysis process of checking human factors requirements or regulations against a given design. We are extending our Parameterized Action Representation (PAR) to store requirements and its execution system to drive human models through required tasks. Databases of actions, objects, regulations, and digital humans are instantiated into PARs and executed by analyzers that simulate the actions on digital humans and monitor the actions to report successes and failures. These extensions will allow quantitative but localized design assessment relative to specific human factors requirements

Avatars á la Snow Crash

We analyzed Neal Stephenson\u27s novel Snow Crash for all references to avatars. This analysis is documented here, including a comparison of the Snow Crash avatars to the current state of real-time virtual human research. The avatar characteristics discussed include appearance, clothing and attachments, ethnicity, locomotion, body actions, forms of communication, and emotion and personality

Simulating Human Activities for Synthetic Inputs to Sensor Systems

We are developing human activity simulations that could be used to test distributed video sensor networks. Our ultimate goals are to build statistical models of pedestrian density and flows at a number of urban locations and to correlate those flows with population movement and density models represented in a spatiotemporal modeling system. In order to create known populace flows, we have built a virtual populace simulation system, called CAROSA, which permits the authoring of functional crowds of people going about role-, context-, and schedule-dependent activities. The capabilities and authoring tools for these functional crowd simulations are described with the intention of readily creating ground truth data for distributed sensor system design and evaluation

Creating Crowd Variation with the Ocean Personality Model

Most current crowd simulators animate homogeneous crowds, but include underlying parameters that can be tuned to create variations within the crowd. These parameters, however, are specific to the crowd models and may be difficult for an animator or naïve user to use. We propose mapping these parameters to personality traits. In this paper, we extend the HiDAC (HighDensity Autonomous Crowds) system by providing each agent with a personality model in order to examine how the emergent behavior of the crowd is affected. We use the OCEAN personality model as a basis for agent psychology. To each personality trait we associate nominal behaviors; thus, specifying personality for an agent leads to an automation of the low-level parameter tuning process. We describe a plausible mapping from personality traits to existing behavior types and analyze the overall emergent crowd behaviors

Being a Part of the Crowd: Towards Validating VR Crowds Using Presence

Crowd simulation models are currently lacking a commonly accepted validation method. In this paper, we propose level of presence achieved by a human in a virtual environment (VE) as a metric for virtual crowd behavior. Using experimental evidence from the presence literature and the results of a pilot experiment that we ran, we explore the egocentric features that a crowd simulation model should have in order to achieve high levels of presence and thus be used as a framework for validation of simulated crowd behavior. We implemented four crowd models for our pilot experiment: social forces, rule based, cellular automata and HiDAC. Participants interacted with the crowd members of each model in an immersive virtual environment for the purpose of studying presence in virtual crowds, with the goal of establishing the basis for a future validation method

Controlling Individual Agents in High-Density Crowd Simulation

Simulating the motion of realistic, large, dense crowds of autonomous agents is still a challenge for the computer graphics community. Typical approaches either resemble particle simulations (where agents lack orientation controls) or are conservative in the range of human motion possible (agents lack psychological state and aren’t allowed to ‘push’ each other). Our HiDAC system (for High-Density Autonomous Crowds) focuses on the problem of simulating the local motion and global wayfinding behaviors of crowds moving in a natural manner within dynamically changing virtual environments. By applying a combination of psychological and geometrical rules with a social and physical forces model, HiDAC exhibits a wide variety of emergent behaviors from agent line formation to pushing behavior and its consequences; relative to the current situation, personalities of the individuals and perceived social density

Feeling crowded? Exploring presence in virtual crowds

Virtual reality experiments with virtual crowds are necessary to study human behavior under panic or stressful situations that cannot be evaluated in the real world (i.e., building evacuation due to fire). In order to carry out those experiments it is necessary to use a crowd simulation model in which a real person is seamlessly immersed and experiences a high sense of presence when interacting with such a crowd. This paper studies several crowd simulation models in order to determine which could best enhance presence for a user within a virtual environment. Egocentric features that affect presence are considered in the evaluation. Once we have a realistic simulation, we could use it to study human behavior and obtain relevant data. That data could then be used to update agent behaviors in the simulation system to further improve the overall realism of large groups of autonomous agents.Postprint (published version

Evaluating American Sign Language Generation Through the Participation of Native ASL Signers

We discuss important factors in the design of evaluation studies for systems that generate animations of American Sign Language (ASL) sentences. In particular, we outline how some cultural and linguistic characteristics of members of the American Deaf community must be taken into account so as to ensure the accuracy of evaluations involving these users. Finally, we describe our implementation and user-based evaluation (by native ASL signers) of a prototype ASL generator to produce sentences containing classifier predicates, frequent and complex spatial phenomena that previous ASL generators have not produced