Visual search in the (un)real world

Kollenberg, Tobit; Neumann, Alexander; Schneider, Dorothe; Tews, Tessa-Karina; Hermann, Thomas; Ritter, Helge; Dierker, Angelika; Koesling, Hendrik

doi:10.1145/1743666.1743696

Cited by 20 publications

(3 citation statements)

References 6 publications

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“…This result is also in line with the better performance seen in a previous study on lightness/color constancy when stimuli were presented in motion [3,4,24,36,37]. A previous study has reported that the visual environments that VR goggles can present are still limited [38]; for example, the field of view is much smaller than that of natural vision at a glance when the head-tracking function is disabled. Considering the integration of lightness information over time [30], the effect of the smooth motion of the image on the HMD screen, generated by the head motions of the viewers, allows the human visual system to access much richer visual information than when using static images on flat computer displays [4][5][6][7][8][14][15][16][17][18][19][20][21][22].…”

Section: Discussionsupporting

confidence: 88%

The Reality of a Head-Mounted Display (HMD) Environment Tested via Lightness Perception

Kuriki,

Sato,

Shioiri

2024

J. Imaging

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Head-mounted displays (HMDs) are becoming more and more popular as a device for displaying a virtual reality space, but how real are they? The present study attempted to quantitatively evaluate the degree of reality achieved with HMDs by using a perceptual phenomenon as a measure. Lightness constancy is an ability that is present in human visual perception, in which the perceived reflectance (i.e., the lightness) of objects appears to stay constant across illuminant changes. Studies on color/lightness constancy in humans have shown that the degree of constancy is high, in general, when real objects are used as stimuli. We asked participants to make lightness matches between two virtual environments with different illuminant intensities, as presented in an HMD. The participants’ matches showed a high degree of lightness constancy in the HMD; our results marked no less than 74.2% (84.8% at the maximum) in terms of the constancy index, whereas the average score on the computer screen was around 65%. The effect of head-tracking ability was confirmed by disabling that function, and the result showed a significant drop in the constancy index but that it was equally effective when the virtual environment was generated by replay motions. HMDs yield a realistic environment, with the extension of the visual scene being accompanied by head motions.

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Section: Discussionsupporting

confidence: 88%

The Reality of a Head-Mounted Display (HMD) Environment Tested via Lightness Perception

Kuriki,

Sato,

Shioiri

2024

J. Imaging

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“…One of the major limitations to our study design is despite the subjects' ability to move their head, the movement is still limited to one plane of motion. With the use of HMD VR goggles, a study in which subjects are free to move in all planes of motion in a 'visual search' task may answer further questions regarding the orienting of attention in realistic scenarios [35,36]. In addition, while the current study attempted to divide the subjects' gaze direction into distinct events, gaze movements in realistic scenarios have been shown to be more complex, with saccade and fixation events constantly interleaving in time [37,38].…”

Section: Limitations/future Directionsmentioning

confidence: 94%

Integrating neural and ocular attention reorienting signals in virtual reality

et al. 2021

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Objective. Reorienting is central to how humans direct attention to diﬀerent stimuli in their environment. Previous studies typically employ well-controlled paradigms with limited eye and head movements to study the neural and physiological processes underlying attention reorienting. Here, we aim to better understand the relationship between gaze and attention reorienting using a naturalistic virtual reality (VR)-based target detection paradigm. Approach. Subjects were navigated through a city and instructed to count the number of targets that appeared on the street. Subjects performed the task in a ﬁxed condition with no head movement and in a free condition where head movements were allowed. Electroencephalography (EEG), gaze and pupil data were collected. To investigate how neural and physiological reorienting signals are distributed across diﬀerent gaze events, we used hierarchical discriminant component analysis (HDCA) to identify EEG and pupil-based discriminating components. Mixedeﬀects general linear models (GLM) were used to determine the correlation between these discriminating components and the diﬀerent gaze events time. HDCA was also used to combine EEG, pupil and dwell time signals to classify reorienting events. Main results. In both EEG and pupil, dwell time contributes most signiﬁcantly to the reorienting signals. However, when dwell times were orthogonalized against other gaze events, the distributions of the reorienting signals were diﬀerent across the two modalities, with EEG reorienting signals leading that of the pupil reorienting signals. We also found that the hybrid classiﬁer that integrates EEG, pupil and dwell time features detects the reorienting signals in both the ﬁxed (AUC = 0.79) and the free (AUC = 0.77) condition. Signiﬁcance. We show that the neural and ocular reorienting signals are distributed diﬀerently across gaze events when a subject is immersed in VR, but nevertheless can be captured and integrated to classify target vs. distractor objects to which the human subject orients.

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“…In contrast to natural viewing, head-mounted displays limit the user's view. This has been observed to lead to less eye rotation and a comparatively larger contribution of head movement to gaze shifts [Kollenberg et al 2010;Pfeil et al 2018]. For this work, we specifically built on quantitative insight into eye, head and torso coordination from a recent study of gaze shifts in VR [Sidenmark and Gellersen 2019a].…”

Section: Related Workmentioning

confidence: 99%

BimodalGaze: Seamlessly Refined Pointing with Gaze and Filtered Gestural Head Movement

Sidenmark

Mardanbegi

Gómez

et al. 2020

ACM Symposium on Eye Tracking Research and Applications

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Figure 1: BimodalGaze enables users to point by gaze and to seamlessly refine the cursor position with head movement. A: In Gaze Mode, the cursor (yellow) follows where the user looks but may not be sufficiently accurate. B: The pointer automatically switches into Head Mode (green) when gestural head movement is detected. C: The pointer automatically switches back into Gaze Mode when the user redirects their attention. Note that the Head Mode is only invoked when needed for adjustment of the cursor. Any natural head movement associated with a gaze shift is filtered and does not cause a mode switch.

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Visual search in the (un)real world

Cited by 20 publications

References 6 publications

The Reality of a Head-Mounted Display (HMD) Environment Tested via Lightness Perception

The Reality of a Head-Mounted Display (HMD) Environment Tested via Lightness Perception

Integrating neural and ocular attention reorienting signals in virtual reality

BimodalGaze: Seamlessly Refined Pointing with Gaze and Filtered Gestural Head Movement

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