Training Efficiently in Virtual Environments: Determinants of Distance Perception of Stationary Observers Viewing Stationary Objects

Abstract

The accurate perception and estimation of distance is an important element of many military tasks. It is necessary for orienting oneself on the battlefield, for making optimal use of terrain features during navigation, and for judging the distance from one point to another. It is also a component of both route and configuration knowledge and acquisition. In order to maximize transfer from Virtual Environment (VE) to the real world, it is important to develop an understanding of the capabilities and limitations of this new training medium. Toward that end, the present study sought to gain insight about the conditions affecting distance estimation of VEs. The purpose of this research is to examine factors that influence the perception of distance in VEs. Two experiments were designed to investigate the relative effects of such factors on distance estimates of a stationary observer positioned at near and medium distances from an object. Factors found to improve distance estimates in these experiments will be incorporated into the design of VEs for subsequent investigations.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1997
Accession Number
ADA337488

Entities

People

  • Bob G. Witmer
  • Paul B. Kline

Organizations

  • U.S. Army Research Institute for the Behavioral and Social Sciences

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • High Resolution
  • Human Factors Engineering
  • Human-Machine Interaction
  • Human-Machine Interfaces
  • Literature Surveys
  • Observation
  • Observers
  • Perception
  • Psychology
  • Simulations
  • Simulators
  • Social Sciences
  • Test And Evaluation
  • Three Dimensional
  • Training
  • Virtual Reality

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.