Title

A Process For Developing Accurate Kinesic Cues In Virtual Environments

Keywords

Behavior Cue Analysis; Computer Animation; Kinesic Cues; Simulation-Based Training

Abstract

Computer animations exhibit the illusion of movements or actions of virtual agents and assets within a virtual environment display. Two distinct animation categories exist: two-dimensional (2D) and three-dimensional (3D). 2D animation is typically stylized and used primarily for entertainment-based efforts such as cartoons and lowfidelity games. 3D animation is applied to a wider variety of domains (e.g., entertainment games, serious games, and training simulations). A well-designed 3D computer animation enables a realistic representation of action portraying the true context of movement, particularly human gestures (Badler, Palmer, & Bindiganavale, 1999). All humans convey intent whether purposefully or not via verbal and non-verbal cues (Bavelas, 1990; Givens, 2002). Kinesic cues convey information to an observer through body language and gestures. Emerging research in training human threat detection requires virtual agents exhibiting kinesic cues to provide visual stimuli within Simulation-Based Training (SBT) applications. Thus, guidelines and specifications for system developers are required. This paper presents a process for defining, designing, and animating kinesic cues using a commercially available software application to mimic realistic human behaviors, movements, and gestures. Through this discussion, culturally agnostic kinesic cues are presented, and relevant limitations are identified. The process described and lessons learned represent a logical progression in the formalization of developing advanced visual models for training Warfighters, law enforcement agents, and first responders to detect and classify human threats.

Publication Date

1-1-2015

Publication Title

24th Conference on Behavior Representation in Modeling and Simulation, BRiMS 2015, co-located with the International Social Computing, Behavioral Modeling and Prediction Conference, SBP 2015

Number of Pages

2-9

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

85006240211 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85006240211

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