Evaluation of X-ray visualization techniques for vertical depth judgments in underground exploration

This paper investigates depth judgment-related performances of X-ray visualization techniques for rendering fully occluded geometries in augmented reality. The techniques we selected for this evaluation are careless overlay ( CO ), edge overlay ( EO ), excavation box ( EB ) and a cross-sectional visualization technique ( CS ). We have designed and conducted a comprehensive user study with 16 participants to examine and analyze the effects related to visualization techniques, having additional virtual objects and the scale of the vertical depths. To the best of our knowledge, this is the first user study on judged vertical depth distances that these techniques were compared against each other. We report our findings using four dependent variables: accuracy, signed error, absolute error and response time to shed some light into real-world performances and also to reveal estimation tendencies of each technique. Our findings suggest similar and better performance for EB , CS compared to CO and EO . We also observed significantly better results for EB and CS techniques when judging Top and Bottom distances compared to Middle distances. Derived from our findings, we proposed a new visualization technique for underground investigation with multiple views. The multi-view technique is our own implementation inspired by magic lens and cross-sectional visualizations with correlating displays.