Binocular eye tracking in VR for visual inspection training

Duchowski, Andrew T.; Medlin, Eric; Gramopadhye, Anand K.; Melloy, Brian J.; Nair, Santosh

doi:10.1145/505009.505010

Cited by 9 publications

(15 citation statements)

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“…This is achieved by mapping gaze deployed on a display to the underlying geometric objects of a 3D scene [Tanriverdi and Jacob 2000;Duchowski et al 2001]. Fisker et al [2013] performed an informal experiment to evaluate the level of comfort these methods offer to the users.…”

Section: Introductionmentioning

confidence: 99%

The effects of fast disparity adjustment in gaze-controlled stereoscopic applications

Bernhard

Dell'mour

Hecher

et al. 2014

Proceedings of the Symposium on Eye Tracking Research and Applications

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With the emergence of affordable 3D displays, stereoscopy is becoming a commodity. However, often users report discomfort even after brief exposures to stereo content. One of the main reasons is the conflict between vergence and accommodation that is caused by 3D displays. We investigate dynamic adjustment of stereo parameters in a scene using gaze data in order to reduce discomfort. In a user study, we measured stereo fusion times after abrupt manipulation of disparities using gaze data. We found that gaze-controlled manipulation of disparities can lower fusion times for large disparities. In addition we found that gaze-controlled disparity adjustment should be applied in a personalized manner and ideally performed only at the extremities or outside the comfort zone of subjects. These results provide important insight on the problems associated with fast disparity manipulation and are essential for developing appealing gaze-contingent and gaze-controlled applications.

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Section: Introductionmentioning

confidence: 99%

The effects of fast disparity adjustment in gaze-controlled stereoscopic applications

Bernhard

Dell'mour

Hecher

et al. 2014

Proceedings of the Symposium on Eye Tracking Research and Applications

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“…If content is already being described by geometries, as it is the case for augmented or virtual reality, this process is simplified. First approaches -also objectcentered -to measure visual attention in virtual reality were using Head-Mounted Displays (HMDs) [Tanriverdi and Jacob 2000;Duchowski et al 2001;Duchowski et al 2004]. Instead of the detour using a recorded image from the scene-camera, the systems could directly use the projection rendered for the particular eye from the framebuffer.…”

Section: Geometry-based Estimation Of the 3d Point Of Regardmentioning

confidence: 99%

“…Thus, the normal picking operations could be used to identify the object below a point of regard. Alternatively, the known position of the eye and the detected 2D fixation on the projection display in the HMD could be used to cast a ray into the 3D world to determine the intersection with the 3D object geometry [Duchowski et al 2001] and thus identify the 3D point of regard and the model of interest.…”

Section: Geometry-based Estimation Of the 3d Point Of Regardmentioning

confidence: 99%

Measuring and visualizing attention in space with 3D attention volumes

Pfeiffer

2012

Proceedings of the Symposium on Eye Tracking Research and Applications

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Knowledge about the point of regard is a major key for the analysis of visual attention in areas such as psycholinguistics, psychology, neurobiology, computer science and human factors. Eye tracking is thus an established methodology in these areas, e.g., for investigating search processes, human communication behavior, product design or human-computer interaction. As eye tracking is a process which depends heavily on technology, the progress of gaze use in these scientific areas is tied closely to the advancements of eyetracking technology. It is thus not surprising that in the last decades, research was primarily based on 2D stimuli and rather static scenarios, regarding both content and observer.Only with the advancements in mobile and robust eye-tracking systems, the observer is freed to physically interact in a 3D target scenario. Measuring and analyzing the point of regards in 3D space, however, requires additional techniques for data acquisition and scientific visualization. We describe the process for measuring the 3D point of regard and provide our own implementation of this process, which extends recent approaches of combining eye tracking with motion capturing, including holistic estimations of the 3D point of regard. In addition, we present a refined version of 3D attention volumes for representing and visualizing attention in 3D space.

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“…Several mobile eye-tracking systems have been developed, including one built by Duchowski and colleagues that is integrated with a virtual reality head-worn display [7] [8]. However, these systems perform offline analysis of the eye movement data to reconstruct gaze direction and point of regard.…”

Section: Related Workmentioning

confidence: 99%

“…We approximated the gaze direction using the head position and orientation [7], as we need only the distance to determine the eye-tracking resolution. We can determine the angle subtended by two 3D points, A and B, where E is the eye origin.…”

Section: Adapting To Eye-tracking Accuracymentioning

confidence: 99%