Improving Spatial Perception for Augmented Reality X-Ray Vision

Abstract

Augmented reality x-ray vision allows users to see through walls and view real occluded objects and locations. We present an augmented reality x-ray vision system that employs multiple view modes to support new visualizations that provide depth cues and spatial awareness to users. The edge overlay visualization provides depth cues to make hidden objects appear to be behind walls, rather than floating in front of them. Utilizing this edge overlay, the tunnel cut-out visualization provides details about occluding layers between the user and remote location. Inherent limitations of these visualizations are addressed by our addition of view modes allowing the user to obtain additional detail by zooming in, or an overview of the environment via an overhead exocentric view.

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

“…Most DR methods require the camera pose or the relative pose of the camera to the scene as an input to recover the hidden background in the current view. Positioning sensors [33,34], visual simultaneous localization and mapping (vSLAM) methods [14,23,27,35,36,43], pre-calibration [6,37], and fidicial markers [31,38] are available. 3.…”

“…Almost all of the existing DR methods allow six degrees of freedom (6DoF) motion for the main camera using positioning sensors [33,34], fiducial markers [22,25,41,49], model-based tracking [13,26], vSLAM [14,23,27,35,44,53], etc. Cosco et al used ARToolKit and ARToolKitPlus markers to track the main camera at pre-observation and run-time for indoor desktop a DR scenario [25,49].…”

“…For example, in the case of [6], the cameras and the target objects are fixed in the environment and the ROI can be set manually. It is not a problem to estimate target areas that are narrower than the actual object area to see part of the wall [33,34,48]. Jarusirisawad and Saito ignored their target objects from a projective grid space (PGS) for their plane sweep algorithm-based 3D reconstruction [29,40].…”

“…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.…”

“…They evaluated whether the observer can intuitively grasp the space and reported the best combination [47]. Avery et al pointed out with a simple transparent representation that information on the wall is lost and that this representation causes problems in the depth perception [34]. Therefore, they proposed a method to show the foreground edges and the background image at the same time to improve the depth perception.…”