158 research outputs found
Emotional Qualities of VR Space
The emotional response a person has to a living space is predominantly
affected by light, color and texture as space-making elements. In order to
verify whether this phenomenon could be replicated in a simulated environment,
we conducted a user study in a six-sided projected immersive display that
utilized equivalent design attributes of brightness, color and texture in order
to assess to which extent the emotional response in a simulated environment is
affected by the same parameters affecting real environments. Since emotional
response depends upon the context, we evaluated the emotional responses of two
groups of users: inactive (passive) and active (performing a typical daily
activity). The results from the perceptual study generated data from which
design principles for a virtual living space are articulated. Such a space, as
an alternative to expensive built dwellings, could potentially support new,
minimalist lifestyles of occupants, defined as the neo-nomads, aligned with
their work experience in the digital domain through the generation of emotional
experiences of spaces. Data from the experiments confirmed the hypothesis that
perceivable emotional aspects of real-world spaces could be successfully
generated through simulation of design attributes in the virtual space. The
subjective response to the virtual space was consistent with corresponding
responses from real-world color and brightness emotional perception. Our data
could serve the virtual reality (VR) community in its attempt to conceive of
further applications of virtual spaces for well-defined activities.Comment: 12 figure
RecolorCloud: A Point Cloud Tool for Recoloring, Segmentation, and Conversion
Point clouds are a 3D space representation of an environment that was
recorded with a high precision laser scanner. These scanners can suffer from
environmental interference such as surface shading, texturing, and reflections.
Because of this, point clouds may be contaminated with fake or incorrect
colors. Current open source or proprietary tools offer limited or no access to
correcting these visual errors automatically.
RecolorCloud is a tool developed to resolve these color conflicts by
utilizing automated color recoloring. We offer the ability to deleting or
recoloring outlier points automatically with users only needing to specify
bounding box regions to effect colors. Results show a vast improvement of the
photo-realistic quality of large point clouds. Additionally, users can quickly
recolor a point cloud with set semantic segmentation colors.Comment: 6 Pages, 9 figures, 1 table, To be submitted to the ACM MMSys 2024
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Power-Ups in Digital Games: The Rewarding Effect of Phantom Game Elementson Player Experience
Power-ups are a type of game reward that allow the player tocustomise their experience by altering gameplay for a shortperiod of time. Despite the wide use of power-ups in videogames, little is known about their effect on gaming experiences.To explore this, we conducted an experimental study that compares the experiences of players depending on their exposureto power-ups in a recreational video game. The results show that players who collected power-ups felt significantly more immersed in the game, experienced more autonomy, but didnot feel more competent or challenged than those who played the game without these collectables. Interestingly, a similareffect was observed for those players who picked up ‘placebo ’power-ups, despite the items having no effect on the gameplay. We provide a discussion of these results and their implications both for games user researchers and game designers
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy
We study gradient descent under linearly correlated noise. Our work is
motivated by recent practical methods for optimization with differential
privacy (DP), such as DP-FTRL, which achieve strong performance in settings
where privacy amplification techniques are infeasible (such as in federated
learning). These methods inject privacy noise through a matrix factorization
mechanism, making the noise linearly correlated over iterations. We propose a
simplified setting that distills key facets of these methods and isolates the
impact of linearly correlated noise. We analyze the behavior of gradient
descent in this setting, for both convex and non-convex functions. Our analysis
is demonstrably tighter than prior work and recovers multiple important special
cases exactly (including anticorrelated perturbed gradient descent). We use our
results to develop new, effective matrix factorizations for differentially
private optimization, and highlight the benefits of these factorizations
theoretically and empirically
The Effects of Object Shape, Fidelity, Color, and Luminance on Depth Perception in Handheld Mobile Augmented Reality
Depth perception of objects can greatly affect a user's experience of an
augmented reality (AR) application. Many AR applications require depth matching
of real and virtual objects and have the possibility to be influenced by depth
cues. Color and luminance are depth cues that have been traditionally studied
in two-dimensional (2D) objects. However, there is little research
investigating how the properties of three-dimensional (3D) virtual objects
interact with color and luminance to affect depth perception, despite the
substantial use of 3D objects in visual applications. In this paper, we present
the results of a paired comparison experiment that investigates the effects of
object shape, fidelity, color, and luminance on depth perception of 3D objects
in handheld mobile AR. The results of our study indicate that bright colors are
perceived as nearer than dark colors for a high-fidelity, simple 3D object,
regardless of hue. Additionally, bright red is perceived as nearer than any
other color. These effects were not observed for a low-fidelity version of the
simple object or for a more-complex 3D object. High-fidelity objects had more
perceptual differences than low-fidelity objects, indicating that fidelity
interacts with color and luminance to affect depth perception. These findings
reveal how the properties of 3D models influence the effects of color and
luminance on depth perception in handheld mobile AR and can help developers
select colors for their applications.Comment: 9 pages, In proceedings of IEEE International Symposium on Mixed and
Augmented Reality (ISMAR) 202
Increasing the Precision of Distant Pointing for Large High-Resolution Displays
Distant pointing at large displays allows rapid cursor movements, but can be problematic when high levels of precision are needed, due to natural hand tremor and track-ing jitter. We present two ray-casting-based interaction techniques for large high-resolution displays – Absolute and Relative Mapping (ARM) Ray-casting and Zooming for Enhanced Large Display Acuity (ZELDA) – that ad-dress this precision problem. ZELDA enhances precision by providing a zoom window, which increases target sizes resulting in greater precision and visual acuity. ARM Ray-casting increases user control over the cursor position by allowing the user to activate and deactivate relative map-ping as the need for precise manipulation arises. The results of an empirical study show that both approaches improve performance on high-precision tasks when compared to basic ray-casting. In realistic use, however, performance of the techniques is highly dependent on user strategy
VALID: A perceptually validated Virtual Avatar Library for Inclusion and Diversity
As consumer adoption of immersive technologies grows, virtual avatars will
play a prominent role in the future of social computing. However, as people
begin to interact more frequently through virtual avatars, it is important to
ensure that the research community has validated tools to evaluate the effects
and consequences of such technologies. We present the first iteration of a new,
freely available 3D avatar library called the Virtual Avatar Library for
Inclusion and Diversity (VALID), which includes 210 fully rigged avatars with a
focus on advancing racial diversity and inclusion. We present a detailed
process for creating, iterating, and validating avatars of diversity. Through a
large online study (n=132) with participants from 33 countries, we provide
statistically validated labels for each avatar's perceived race and gender.
Through our validation study, we also advance knowledge pertaining to the
perception of an avatar's race. In particular, we found that avatars of some
races were more accurately identified by participants of the same race
(Amplified) Banded Matrix Factorization: A unified approach to private training
Matrix factorization (MF) mechanisms for differential privacy (DP) have
substantially improved the state-of-the-art in privacy-utility-computation
tradeoffs for ML applications in a variety of scenarios, but in both the
centralized and federated settings there remain instances where either MF
cannot be easily applied, or other algorithms provide better tradeoffs
(typically, as becomes small). In this work, we show how MF can
subsume prior state-of-the-art algorithms in both federated and centralized
training settings, across all privacy budgets. The key technique throughout is
the construction of MF mechanisms with banded matrices (lower-triangular
matrices with at most nonzero bands including the main diagonal). For
cross-device federated learning (FL), this enables multiple-participations with
a relaxed device participation schema compatible with practical FL
infrastructure (as demonstrated by a production deployment). In the centralized
setting, we prove that banded matrices enjoy the same privacy amplification
results as the ubiquitous DP-SGD algorithm, but can provide strictly better
performance in most scenarios -- this lets us always at least match DP-SGD, and
often outperform it.Comment: 34 pages, 13 figure
VALID: a perceptually validated Virtual Avatar Library for Inclusion and Diversity
As consumer adoption of immersive technologies grows, virtual avatars will play a prominent role in the future of social computing. However, as people begin to interact more frequently through virtual avatars, it is important to ensure that the research community has validated tools to evaluate the effects and consequences of such technologies. We present the first iteration of a new, freely available 3D avatar library called the Virtual Avatar Library for Inclusion and Diversity (VALID), which includes 210 fully rigged avatars with a focus on advancing racial diversity and inclusion. We also provide a detailed process for creating, iterating, and validating avatars of diversity. Through a large online study (n = 132) with participants from 33 countries, we provide statistically validated labels for each avatar’s perceived race and gender. Through our validation study, we also advance knowledge pertaining to the perception of an avatar’s race. In particular, we found that avatars of some races were more accurately identified by participants of the same race
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