Exploring legibility of augmented reality X-ray

Abstract

Virtual objects can be visualized inside real objects using augmented reality (AR). This visualization is called AR X-ray because it gives the impression of seeing through the real object. In standard AR, virtual information is overlaid on top of the real world. To position a virtual object inside an object, AR X-ray requires partially occluding the virtual object with visually important regions of the real object. In effect, the virtual object becomes less legible compared to when it is completely unoccluded. Legibility is an important consideration for various applications of AR X-ray. In this research, we explored legibility in two implementations of AR X-ray, namely, edge-based and saliency-based. In our first experiment, we explored on the tolerable amounts of occlusion to comfortably distinguish small virtual objects. In our second experiment, we compared edge-based and saliency-based AR X-ray methods when visualizing virtual objects inside various real objects. Moreover, we benchmarked the legibility of these two methods against alpha blending. From our experiments, we observed that users have varied preferences for proper amounts of occlusion cues for both methods. The partial occlusions generated by the edgebased and saliency-based methods need to be adjusted depending on the lighting condition and the texture complexity of the occluding object. In most cases, users identify objects faster with saliency-based AR X-ray than with edge-based AR X-ray. Insights from this research can be directly applied to the development of AR X-ray applications.

Survey on depth perception in head mounted displays: distance estimation in virtual reality, augmented reality, and mixed reality

“…Three different objects with multiple sizes were used to visualise 3D objects in HMDs and assess their depth perception accuracy. Santos et al [46] studied occlusion as a depth cue to introduce and enhance depth perception in AR X‐ray systems. Their focus was on how different amounts of occlusion will influence depth perception performance.…”

A survey of diminished reality: Techniques for visually concealing, eliminating, and seeing through real objects

“…These techniques are called see-through vision [46,47], AR X-ray [33,34,48,[71][72][73], and ghosted views [74]. These representation methods will be useful for avoiding the danger of a collision with the diminished objects.…”

“…Therefore, in such the case, it is necessary to perform a user study to evaluate whether or not the implemented DR method was able to output a visually convincing result. These evaluation methods are often used in literature related to seethrough processing [33,34,[46][47][48][71][72][73][74], and they are helpful.…”

A Work Area Visualization by Multi-View Camera-Based Diminished Reality

“…For example, when the electric device the user held was removed completely, the user became confused, since the user's hand and tool were invisible. Buchmann et al [5] discussed similar results; their basic solution was to use semi-transparent representation, which is the de facto standard for representing an object to be removed as semi-transparent (for example, the AR X-ray [28,29] and See-through Vision [12,30]). …”