Eye tracking for locomotion prediction in redirected walking

Zank, Markus; Kunz, Andreas

doi:10.1109/3dui.2016.7460030

Cited by 29 publications

(21 citation statements)

References 25 publications

(37 reference statements)

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“…Eye trackers have become more prevalent in 3D environments such as VR with several commercial products available such as the HoloLens 2, HTC Vive Pro Eye and the FOVE 0. This development has sparked an increase in eye tracking research in 3D environments, and eye tracking has been used for measuring and leveraging gaze behaviour [1,2,47,48], foveated rendering [38], as well as redirected walking [58].…”

Section: Gaze Interaction In 3d Environmentsmentioning

confidence: 99%

Eye&Head

Sidenmark

Gellersen

2019

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

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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.

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Section: Gaze Interaction In 3d Environmentsmentioning

confidence: 99%

Eye&Head

Sidenmark

Gellersen

2019

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

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“…Steering Algorithms: In order to calculate the amount of redirection, two parameters are required: the target direction of the user (a) in the VE, and (b) in the PTS. There are many methods for predicting the target direction in VE ranging from using the user's past walking direction [57], to head rotations [46], and gaze direction [58]. As there are spatial constraints in terms of the available PTS, the user must be steered away from the boundaries of the PTS i.e.…”

Section: Steering Algorithms Resetting Phase and Natural Visual Suppmentioning

confidence: 99%

Inattentional Blindness for Redirected Walking Using Dynamic Foveated Rendering

Joshi

Poullis

2020

IEEE Access

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Figure 1: Left: Orientation-based redirection using dynamic-foveated rendering which leverages the effect of inattentional blindness induced by a cognitive task. The blending (e.g. parallax of green alien) in the transition zone between the rotated virtual environment (VE) (non-foveal) and the non-rotated VE (foveal) is imperceptible by the users due to inattentional blindness. Right: The path walked in physical tracked space (PTS) up to that point is shown in orange color. The corresponding path in the VE is shown in blue color. The cyan-colored box indicates the 4 × 4m 2 available PTS and the camera icon inside the box indicates the location of the user w.r.t. the PTS. Even with room-scale PTS such as the one used, the users were able to walk distances in the virtual environment (VE) which are up to almost 18× orders of magnitude higher than the longest distance in the PTS; maximum recorded in experiments was 103.9m. Angular gain for the frame shown is at its maximum i.e. 13.5 • . ABSTRACTRedirected walking is a Virtual Reality(VR) locomotion technique which enables users to navigate virtual environments (VEs) that are spatially larger than the available physical tracked space.In this work we present a novel technique for redirected walking in VR based on the psychological phenomenon of inattentional blindness. Based on the user's visual fixation points we divide the user's view into zones. Spatially-varying rotations are applied according to the zone's importance and are rendered using foveated rendering. Our technique is real-time and applicable to small and large physical spaces. Furthermore, the proposed technique does not require the use of stimulated saccades but rather takes advantage of naturally occurring saccades and blinks for a complete refresh of the framebuffer. We performed extensive testing and present the analysis of the results of three user studies conducted for the evaluation.

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“…After more simple approaches of predicting a user's locomotion like [11,14,15], which are mainly based on extrapolating the user's current or recent movement, there is recent work by Gandrud et al [4] and Zank et al [16,17]. Here, eye tracking or models of human locomotion are used to provide a more sophisticated prediction of a user's destination that incorporates knowledge of human locomotion as well as the Virtual Environment into the prediction.…”

Section: Predictionmentioning

confidence: 99%

“…They use the fact that human locomotion is stereotypical [5], which allows generic models of human locomotion to be combined with predefined target points to assign probabilities to individual targets. Other approaches also use distinct target locations in combination with eye tracking to estimate the user's intention [4,17].…”

Section: Introductionmentioning

confidence: 99%

Optimized graph extraction and locomotion prediction for redirected walking

Zank

Kunz

2017

2017 IEEE Symposium on 3D User Interfaces (3DUI)

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Redirected walking with advanced planners such as MPCRed or FORCE requires both knowledge about the virtual environmentmostly in the form of a skeleton graph representing the virtual environment -and a robust prediction of the user's actions. This paper presents methods for both parts and evaluates them with a number of test cases.Since frame rate is crucial for a virtual reality application, the computationally heavy extraction and preprocessing of the skeleton graph is done offline while only parts directly linked to the user's behavior such as the prediction are done online. The prediction is done using a target-based long-term prediction and the targets are determined automatically and combined with targets predefined by the designer of the virtual environment.The methods presented here provide a graph that is well suited for planning redirection and allows prediction techniques previously only demonstrated in studies to be applied to large scale virtual environments.

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Eye tracking for locomotion prediction in redirected walking

Cited by 29 publications

References 25 publications

Eye&Head

Eye&Head

Inattentional Blindness for Redirected Walking Using Dynamic Foveated Rendering

Optimized graph extraction and locomotion prediction for redirected walking

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