Camera-Based Selection with Low-Cost Mobile VR Head-Mounted Displays

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Luo, Siqi




I present a study comparing selection techniques for low-cost mobile VR devices, such as Google Cardboard. My objective was to assess if alternatives to common head-ray selection methods were feasible with current computer vision tracking approaches on the mobile. In the first experiment, I compared three selection techniques, air touch, head ray, and finger ray. Overall, hand-based selection technique (air touch) performed much worse than ray-based selection techniques. In the second experiment, I compared different combinations of selection techniques and selection activation methods. Results indicated that the built-in Cardboard button worked well with head ray and hand gesture with ray-based techniques can be an interaction potential on mobile VR. I concluded that camera-based ray selection techniques and hand-based activation mechanism are promising on Mobile VR in the future.


Computer Science




Carleton University

Thesis Degree Name: 

Master of Computer Science: 

Thesis Degree Level: 


Thesis Degree Discipline: 

Human-Computer Interaction

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Theses and Dissertations

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