HYBRID METHOD FOR DETECTING INFLUENTIAL FACTORS FOR TRACKING CAMERAS IN A CAVE

摘要

The industrial world increasingly uses Virtual Reality technology in design and research processes, in order to improve quality, but also to stick to the concept of a green technology. The accuracy and precision of VR systems such as the Cave Automatic Virtual Environment (CAVE), directly influences the range of possibilities of these processes. So, the aim of this paper is to describe a hybrid method (Monte Carlo Method and Design Of Experiment using Hadamard matrix) used to adjust tracking system cameras in a CAVE. A model of the tracking system is created based on factors of the camera, adjustable or not. This method provides a classification in order of influence of these adjustable factors over the CAVE tracking accuracy. This hybrid method also improves the accuracy of the VR system from Aix Marseille Universite and to run the application of a knee surgery with high quality of immersion.