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Augmented Reality (AR) see-through vision is an interesting research topicsince it enables users to see through a wall and see the occluded objects. Mostexisting research focuses on the visual effects of see-through vision, whilethe interaction method is less studied. However, we argue that using commoninteraction modalities, e.g., midair click and speech, may not be the optimalway to control see-through vision. This is because when we want to see throughsomething, it is physically related to our gaze depth/vergence and thus shouldbe naturally controlled by the eyes. Following this idea, this paper proposes anovel gaze-vergence-controlled (GVC) see-through vision technique in AR. Sincegaze depth is needed, we build a gaze tracking module with two infrared camerasand the corresponding algorithm and assemble it into the Microsoft HoloLens 2to achieve gaze depth estimation. We then propose two different GVC modes forsee-through vision to fit different scenarios. Extensive experimental resultsdemonstrate that our gaze depth estimation is efficient and accurate. Bycomparing with conventional interaction modalities, our GVC techniques are alsoshown to be superior in terms of efficiency and more preferred by users.Finally, we present four example applications of gaze-vergence-controlledsee-through vision.

Gaze-Vergence-Controlled See-Through Vision in Augmented Reality