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

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

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

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

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

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

Generating Plausible Individual Agent Movements From Spatio-Temporal Occupancy Data

We introduce the Spatio-Temporal Agent Motion Model, a datadriven representation of the behavior and motion of individuals within a space over the course of a day. We explore different representations for this model, incorporating different modes of individual behavior, and describe how crowd simulations can use this model as source material for dynamic and realistic behaviors

Real Time Virtual Humans

The last few years have seen great maturation in the computation speed and control methods needed to portray 3D virtual humans suitable for real interactive applications. Various dimensions of real-time virtual humans are considered, such as appearance and movement, autonomous action, and skills such as gesture, attention, and locomotion. A virtual human architecture includes low level motor skills, mid-level PaT-Net parallel finite-state machine controller, and a high level conceptual action representation that can be used to drive virtual humans through complex tasks. This structure offers a deep connection between natural language instructions and animation control