SharpView: Improved clarity of defocussed content on optical see-through head-mounted displays

Oshima, Kohei; Moser, Kenneth R.; Rompapas, Damien Constantine; Swan, J. Edward; Ikeda, Sei; Yamamoto, Go; Taketomi, Takafumi; Sandor, Christian; Kato, Hirokazu

doi:10.1109/vr.2016.7504749

Cited by 20 publications

(17 citation statements)

References 3 publications

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“…This is likely because the estimated amount of blur did not perfectly match the amount of blur perceived by participants. This coincides with the observation made in [39]. In our trials, participants could always find the virtual objects.…”

Section: Correcting Screen-object Disparitysupporting

confidence: 92%

“…Second, we plan to integrate EyeAR into an OST-HMD by either miniaturizing, or replicating, the function of the autorefractometer, for example through use of eye tracking cameras as described in [36,37,39]. Third, we will refine our methodology for conducting AR Turing Tests and carry out several more.…”

Section: Discussionmentioning

confidence: 99%

“…Some methods use the variance in the reflection of infrared LEDs on the lens of the eye to estimate the focus depth [36]. Others distinguish between different focus planes [37,38] or estimate the focus through intersection of the gaze with scene geometry [39]. However, they do not provide continuous measurements that are necessary for correct DoF representation.…”

Section: Measuring the Eyementioning

confidence: 99%

“…As an alternative, we tried SharpView [39]. SharpView estimates the amount of blur caused by the difference between a user's focus distance and the screen location.…”

Section: Correcting Screen-object Disparitymentioning

confidence: 99%

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EyeAR: Refocusable Augmented Reality Content through Eye Measurements

Rompapas

Rovira

Plopski

et al. 2017

MTI

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Augmented Reality (AR) superimposes computer graphics (CG) onto a user's view of the real world. A key quality problem in this field is to achieve coherence between reality and CG when the user's eyes refocus or change pupil size. We designed and evaluated a display that improves coherence by measuring the user's eye state and continuously adapting CG accordingly. Our tabletop prototype emulates an Optical See-Through Head-Mounted Display, a common AR display device. In our evaluation, participants observed three pillars at different depths. We then challenged them to identify a virtual pillar among the three while freely refocusing their eyes. Results show that our design significantly improved realism. Compared to Light Field Displays, our design aims to simplify display-optics while providing similar quality. We could only partially achieve this goal. We discuss the lessons we learned and how we plan to overcome the remaining challenges. The experimental protocol from our evaluation is useful for display developers as it can be used to measure the coherence of a display.

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Section: Correcting Screen-object Disparitysupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Measuring the Eyementioning

confidence: 99%

“…As an alternative, we tried SharpView [39]. SharpView estimates the amount of blur caused by the difference between a user's focus distance and the screen location.…”

Section: Correcting Screen-object Disparitymentioning

confidence: 99%

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EyeAR: Refocusable Augmented Reality Content through Eye Measurements

Rompapas

Rovira

Plopski

et al. 2017

MTI

Self Cite

View full text Add to dashboard Cite

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“…The major technological limitations of commercial OST HMDs, are due to their general-purpose nature and the lack of a standardized software framework for medical applications. As regards the first limitation, AR headsets were, and still are, mostly designed for parallel viewing: the virtual content is projected at a fixed focal distance (normally between 2 m and infinity), and therefore they generate perceptual conflicts, such as vergence-accommodation conflict and focus rivalry [15], [16], when used to interact with objects closer to the viewer's eyes (i.e., at arm's reach) [17]. In addition, when embedded with tracking sensors and computing units, they are generally quite cumbersome and thus rather uncomfortable for a prolonged use with the head tilted such as during manual tasks.…”

Section: Introductionmentioning

confidence: 99%

Software Framework for Customized Augmented Reality Headsets in Medicine

et al. 2020

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The growing availability of self-contained and affordable augmented reality headsets such as the Microsoft HoloLens is encouraging the adoption of these devices also in the healthcare sector. However, technological and human-factor limitations still hinder their routine use in clinical practice. Among them, the major drawbacks are due to their general-purpose nature and to the lack of a standardized framework suited for medical applications and devoid of platform-dependent tracking techniques and/or complex calibration procedures. To overcome such limitations, in this paper we present a software framework that is designed to support the development of augmented reality applications for custom-made headmounted displays designed to aid high-precision manual tasks. The software platform is highly configurable, computationally efficient, and it allows the deployment of augmented reality applications capable to support in situ visualization of medical imaging data. The framework can provide both optical and video see-throughbased augmentations and it features a robust optical tracking algorithm. An experimental study was designed to assess the efficacy of the platform in guiding a simulated task of surgical incision. In the experiments, the user was asked to perform a digital incision task, with and without the aid of the augmented reality headset. The task accuracy was evaluated by measuring the similarity between the traced curve and the planned one. The average error in the augmented reality tests was < 1 mm. The results confirm that the proposed framework coupled with the new-concept headset may boost the integration of augmented reality headsets into routine clinical practice.

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Effect of immersive visualization technologies on cognitive load, motivation, usability, and embodiment

et al. 2021

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Virtual reality (VR) is a promising tool to promote motor (re)learning in healthy users and brain-injured patients. However, in current VR-based motor training, movements of the users performed in a three-dimensional space are usually visualized on computer screens, televisions, or projection systems, which lack depth cues (2D screen), and thus, display information using only monocular depth cues. The reduced depth cues and the visuospatial transformation from the movements performed in a three-dimensional space to their two-dimensional indirect visualization on the 2D screen may add cognitive load, reducing VR usability, especially in users suffering from cognitive impairments. These 2D screens might further reduce the learning outcomes if they limit users’ motivation and embodiment, factors previously associated with better motor performance. The goal of this study was to evaluate the potential benefits of more immersive technologies using head-mounted displays (HMDs). As a first step towards potential clinical implementation, we ran an experiment with 20 healthy participants who simultaneously performed a 3D motor reaching and a cognitive counting task using: (1) (immersive) VR (IVR) HMD, (2) augmented reality (AR) HMD, and (3) computer screen (2D screen). In a previous analysis, we reported improved movement quality when movements were visualized with IVR than with a 2D screen. Here, we present results from the analysis of questionnaires to evaluate whether the visualization technology impacted users’ cognitive load, motivation, technology usability, and embodiment. Reports on cognitive load did not differ across visualization technologies. However, IVR was more motivating and usable than AR and the 2D screen. Both IVR and AR rea ched higher embodiment level than the 2D screen. Our results support our previous finding that IVR HMDs seem to be more suitable than the common 2D screens employed in VR-based therapy when training 3D movements. For AR, it is still unknown whether the absence of benefit over the 2D screen is due to the visualization technology per se or to technical limitations specific to the device.

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SharpView: Improved clarity of defocussed content on optical see-through head-mounted displays

Cited by 20 publications

References 3 publications

EyeAR: Refocusable Augmented Reality Content through Eye Measurements

EyeAR: Refocusable Augmented Reality Content through Eye Measurements

Software Framework for Customized Augmented Reality Headsets in Medicine

Effect of immersive visualization technologies on cognitive load, motivation, usability, and embodiment

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