Registration Error Analysis for Augmented Reality

Author:

Holloway Richard L.1

Affiliation:

1. Department of Computer Science, University of North Carolina, Chapel Hill, NC 27514.

Abstract

Augmented reality (AR) systems typically use see-through head-mounted displays (STHMDs) to superimpose images of computer-generated objects onto the user's view of the real environment in order to augment it with additional information. The main failing of current AR systems is that the virtual objects displayed in the STHMD appear in the wrong position relative to the real environment. This registration error has many causes: system delay, tracker error, calibration error, optical distortion, and misalignment of the model, to name only a few. Although some work has been done in the area of system calibration and error correction, very little work has been done on characterizing the nature and sensitivity of the errors that cause misregistration in AR systems. This paper presents the main results of an end-to-end error analysis of an optical STHMD-based tool for surgery planning. The analysis was done with a mathematical model of the system and the main results were checked by taking measurements on a real system under controlled circumstances. The model makes it possible to analyze the sensitivity of the system-registration error to errors in each part of the system. The major results of the analysis are: (1) Even for moderate head velocities, system delay causes more registration error than all other sources combined; (2) eye tracking is probably not necessary; (3) tracker error is a significant problem both in head tracking and in system calibration; (4) the World (or reference) coordinate system adds error and should be omitted when possible; (5) computational correction of optical distortion may introduce more delay-induced registration error than the distortion error it corrects, and (6) there are many small error sources that will make submillimeter registration almost impossible in an optical STHMD system without feedback. Although this model was developed for optical STHMDs for surgical planning, many of the results apply to other HMDs as well.

Publisher

MIT Press - Journals

Subject

Computer Vision and Pattern Recognition,Human-Computer Interaction,Control and Systems Engineering,Software

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