Predator-prey vision metaphor for multi-tasking virtual environments

Sherstyuk, A.; Treskunov, Anton; Gavrilova, Marina

doi:10.1109/3dui.2012.6184188

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…More recently, virtual lens systems have been studied in more detail for the purposes of looking through to another "dimension" of data by Looser et al [18]. Zooming interfaces for tablets by Mulloni et al [22], and using head tracking in a VR environment for the purposes of modifying or magnifying the current FOV by both Sherstyuk et al and Yano et al have also been proposed [29] [34].…”

Section: Transitioning and Merging Augmentative Datamentioning

confidence: 99%

ModulAR: Eye-Controlled Vision Augmentations for Head Mounted Displays

Orlosky

Toyama

Kiyokawa

et al. 2015

IEEE Trans. Visual. Comput. Graphics

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In the last few years, the advancement of head mounted display technology and optics has opened up many new possibilities for the field of Augmented Reality. However, many commercial and prototype systems often have a single display modality, fixed field of view, or inflexible form factor. In this paper, we introduce Modular Augmented Reality (ModulAR), a hardware and software framework designed to improve flexibility and hands-free control of video see-through augmented reality displays and augmentative functionality. To accomplish this goal, we introduce the use of integrated eye tracking for on-demand control of vision augmentations such as optical zoom or field of view expansion. Physical modification of the device's configuration can be accomplished on the fly using interchangeable camera-lens modules that provide different types of vision enhancements. We implement and test functionality for several primary configurations using telescopic and fisheye camera-lens systems, though many other customizations are possible. We also implement a number of eye-based interactions in order to engage and control the vision augmentations in real time, and explore different methods for merging streams of augmented vision into the user's normal field of view. In a series of experiments, we conduct an in depth analysis of visual acuity and head and eye movement during search and recognition tasks. Results show that methods with larger field of view that utilize binary on/off and gradual zoom mechanisms outperform snapshot and sub-windowed methods and that type of eye engagement has little effect on performance.

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Section: Transitioning and Merging Augmentative Datamentioning

confidence: 99%