Demo Data from SIGIR 2026 / reviewers in the wild / expert
Dennis M. Levi
dblp:259/8661
· DBLP profile ↗
3ranked-venue papers
0as first author
2since 2021 · last 2024
0000-0002-5350-8639ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Usability and user experience research · 56% Immersive interaction · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Usability and user experience research › visual perception
vergence-accommodation conflict |
0.7 | 1 | 2023 | The Statistics of Eye Movements and Binocular Disparities during VR Gaming: Implications for Headset Design · ACM Trans. Graph. 2023 |
Immersive interaction
virtual reality |
0.7 | 1 | 2023 | The Statistics of Eye Movements and Binocular Disparities during VR Gaming: Implications for Headset Design · ACM Trans. Graph. 2023 |
Usability and user experience research › user perception
user comfort |
0.2 | 1 | 2023 | The Statistics of Eye Movements and Binocular Disparities during VR Gaming: Implications for Headset Design · ACM Trans. Graph. 2023 |
Methods — techniques the papers use, named apart from their topics
eye movement statistics · 0.7binocular disparity analysis · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | The Effect of Interocular Contrast Differences on the Appearance of Augmented Reality ImageryabstractAugmented reality (AR) devices seek to create compelling visual experiences that merge virtual imagery with the natural world. These devices often rely on wearable near-eye display systems that can optically overlay digital images to the left and right eyes of the user separately. Ideally, the two eyes should be shown images with minimal radiometric differences (e.g., the same overall luminance, contrast, and color in both eyes), but achieving this binocular equality can be challenging in wearable systems with stringent demands on weight and size. Basic vision research has shown that a spectrum of potentially detrimental perceptual effects can be elicited by imagery with radiometric differences between the eyes, but it is not clear whether and how these findings apply to the experience of modern AR devices. In this work, we first develop a testing paradigm for assessing multiple aspects of visual appearance at once, and characterize five key perceptual factors when participants viewed stimuli with interocular contrast differences. In a second experiment, we simulate optical see-through AR imagery using conventional desktop LCD monitors and use the same paradigm to evaluate the multi-faceted perceptual implications when the AR display luminance differs between the two eyes. We also include simulations of monocular AR systems (i.e., systems in which only one eye sees the displayed image). Our results suggest that interocular contrast differences can drive several potentially detrimental perceptual effects in binocular AR systems, such as binocular luster, rivalry, and spurious depth differences. In addition, monocular AR displays tend to have more artifacts than binocular displays with a large contrast difference in the two eyes. A better understanding of the range and likelihood of these perceptual phenomena can help inform design choices that support high-quality user experiences in AR. Minqi Wang, Dennis M. Levi, Emily A. Cooper |
ACM Trans. Appl. Percept. | 3 |
| 2023 | The Statistics of Eye Movements and Binocular Disparities during VR Gaming: Implications for Headset DesignabstractThe human visual system evolved in environments with statistical regularities. Binocular vision is adapted to these such that depth perception and eye movements are more precise, faster, and performed comfortably in environments consistent with the regularities. We measured the statistics of eye movements and binocular disparities in virtual-reality (VR) - gaming environments and found that they are quite different from those in the natural environment. Fixation distance and direction are more restricted in VR, and fixation distance is farther. The pattern of disparity across the visual field is less regular in VR and does not conform to a prominent property of naturally occurring disparities. From this we predict that double vision is more likely in VR than in the natural environment. We also determined the optimal screen distance to minimize discomfort due to the vergence-accommodation conflict, and the optimal nasal-temporal positioning of head-mounted display (HMD) screens to maximize binocular field of view. Finally, in a user study we investigated how VR content affects comfort and performance. Content that is more consistent with the statistics of the natural world yields less discomfort than content that is not. Furthermore, consistent content yields slightly better performance than inconsistent content. Avi M. Aizenman, George Alex Koulieris, Agostino Gibaldi, Vibhor Sehgal, Dennis M. Levi, Martin S. Banks |
ACM Trans. Graph. | 5 |
| 2007 | Feasibility Study on a Hyperacuity Device With Motion Uncertainty: Two-Point StimuliabstractCan a device that can perform hyperacuity vision tasks be built? In this paper, a feasibility study based on separation discrimination is conducted. Two types of ideal detectors are considered. The first is the stimulus defined statistically (SDS) detector by Geisler and Davilla. The second is one that estimates the uncertainty and then takes out its effect. In the first method, an array of many ideal stimulus defined exactly (SDE) detectors covers uncertainties and forms the ideal SDS detector. When the separation distance between the SDE detectors is around 1 arcmin, the SDS detector can achieve nearly optimal performance. To cover the motion uncertainty with nearly optimal performance, the SDE detector at each position needs to cover 16 directions, and at each direction, it needs to cover speeds with an increment of 0.5 degrees/s. Typically, the SDS detector needs 7776 SDE detectors to deal with a speed up to 2 degrees/s stimulus movement with a randomly selected direction and a 9 min x 9 min position uncertainty region. This ideal observer can achieve a hyperacuity threshold of 2-4 arcsec. Its threshold is almost constant over the range of speeds covered by the SDS detector. Using the second method, position estimation and motion tracking capability is examined. With perfect position estimation and motion tracking, the SDS detector can be reduced to a single SDE detector that is tuned to correct position and motion direction and speed. Two lower bounds on the estimation variance are examined, namely: 1) the Cramer-Rao bound and 2) the Ziv-Zakai bound. The results showed that if an estimation algorithm that can achieve the performance of bounds can be found, then the second method could achieve a hyperacuity capability of 1 s or less. The human visual system may more likely adopt the first method, but the second is simpler to use in building up a device using microprocessors. In this paper, dot-pair templates are used, which precisely match to dot-pair stimuli, to compute the likelihood and make a decision. The main difference between this paper and that of Geisler and Davilla lies in using a discrete sum over an array of SDE detectors to closely approximate continuous integration over the uncertain region, which makes it much easier in hardware implementation. Lei Wei 0003, Dennis M. Levi, Roger W. Li, Stanley A. Klein |
IEEE Trans. Syst. Man Cybern. Part B | 2 |