Resolving Target Ambiguity in 3D Gaze Interaction through VOR Depth Estimation

Mardanbegi, Diako; Langlotz, Tobias; Gellersen, Hans

doi:10.1145/3290605.3300842

Cited by 24 publications

(30 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These methods exploit eye-head coordination implicitly as they track the compensatory eye movement during a head gesture, without need for separate head tracking. In extension, head turning has been proposed for scalar input to controls fixated by gaze [36] and 3D target disambiguation [28]. In Eye-SeeThrough, head movement controls a toolglass that can be moved over gaze-fixated targets [29].…”

Section: Combination Of Eye and Head Movementmentioning

confidence: 99%

Eye&Head

Sidenmark

Gellersen

2019

Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology

Self Cite

View full text Add to dashboard Cite

Eye gaze involves the coordination of eye and head movement to acquire gaze targets, but existing approaches to gaze pointing are based on eye-tracking in abstraction from head motion. We propose to leverage the synergetic movement of eye and head, and identify design principles for Eye&Head gaze interaction. We introduce three novel techniques that build on the distinction of head-supported versus eyes-only gaze, to enable dynamic coupling of gaze and pointer, hover interaction, visual exploration around pre-selections, and iterative and fast confirmation of targets. We demonstrate Eye&Head interaction on applications in virtual reality, and evaluate our techniques against baselines in pointing and confirmation studies. Our results show that Eye&Head techniques enable novel gaze behaviours that provide users with more control and flexibility in fast gaze pointing and selection.

show abstract

Section: Combination Of Eye and Head Movementmentioning

confidence: 99%

Eye&Head

Sidenmark

Gellersen

2019

Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology

Self Cite

View full text Add to dashboard Cite

show abstract

“…These early works demonstrated how target distance affects the VOR gain for angular horizontal movements. Recent work showed that the effect can be used for resolving target ambiguity when gaze is used for object selection in virtual reality [Mardanbegi et al 2019]. This work, in contrast, presents a fundamental investigation of VOR for gaze depth estimation for which we build on a theory developed in other fields, i.e.…”

Section: Related Workmentioning

confidence: 99%

“…The raw pupil position data was less noisy than the gaze signal for some of the recordings. As suggested in [Mardanbegi et al 2019], we also used pupil data instead of gaze data. Being able to use the pupil position makes the proposed method independent from gaze calibration.…”

Section: Vor Gain Using Pupil Centrementioning

confidence: 99%

“…causing target ambiguity [Deng et al 2017;Mardanbegi et al 2019]. It is therefore of interest to estimate fixation depth directly based on information from the eyes.…”

mentioning

confidence: 99%

“…Recent work proposed the use of VOR to disambiguate targets selected by gaze in virtual reality [Mardanbegi et al 2019]. The purpose of this work is to provide a fundamental exploration of VOR gain for gaze depth estimation.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Monocular gaze depth estimation using the vestibulo-ocular reflex

Mardanbegi

Clarke

Gellersen

2019

Proceedings of the 11th ACM Symposium on Eye Tracking Research &Amp; Applications

Self Cite

View full text Add to dashboard Cite

Gaze depth estimation presents a challenge for eye tracking in 3D. This work investigates a novel approach to the problem based on eye movement mediated by the vestibulo-ocular reflex (VOR). VOR stabilises gaze on a target during head movement, with eye movement in the opposite direction, and the VOR gain increases the closer the fixated target is to the viewer. We present a theoretical analysis of the relationship between VOR gain and depth which we investigate with empirical data collected in a user study (N=10). We show that VOR gain can be captured using pupil centres, and propose and evaluate a practical method for gaze depth estimation based on a generic function of VOR gain and two-point depth calibration. The results show that VOR gain is comparable with vergence in capturing depth while only requiring one eye, and provide insight into open challenges in harnessing VOR gain as a robust measure.

show abstract

For higher accuracy: 3D eye movement gaze depth estimation method based on Mix-TCN

Zhu

2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Currently, the biggest obstacle in applying eye tracking technology in Virtual Reality (VR) and Augmented Reality (AR) scenes is the particular difficulty in choosing distance and object distance in 3D scenes. In previous research, geometric calculation methods using vestibular ocular reflex (VOR) and research on binocular visual angle have been studied to some extent, but unfortunately, their effects have not reached a practical level. The paper proposes a new research idea to estimate the depth of binocular gaze using a method of time series eye movement data analysis based on depth learning, and proposes a Mix-Temporal Convolutional Network (TCN) optical time series network. By combining VOR and deep learning theory, the paper has realized the current state-of-the-art technology for estimating the depth of gaze from the movement of the gaze.

show abstract

Resolving Target Ambiguity in 3D Gaze Interaction through VOR Depth Estimation

Cited by 24 publications

References 39 publications

Eye&Head

Eye&Head

Monocular gaze depth estimation using the vestibulo-ocular reflex

For higher accuracy: 3D eye movement gaze depth estimation method based on Mix-TCN

Contact Info

Product

Resources

About