多媒体学术速递[1.10]
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cs.MM多媒体，共计3篇
【1】 Security Considerations for Virtual Reality Systems
标题：虚拟现实系统的安全注意事项
链接：https://arxiv.org/abs/2201.02563
摘要：There is a growing need for authentication methodology in virtual reality
applications. Current systems assume that the immersive experience technology
is a collection of peripheral devices connected to a personal computer or
mobile device. Hence there is a complete reliance on the computing device with
traditional authentication mechanisms to handle the authentication and
authorization decisions. Using the virtual reality controllers and headset
poses a different set of challenges as it is subject to unauthorized
observation, unannounced to the user given the fact that the headset completely
covers the field of vision in order to provide an immersive experience. As the
need for virtual reality experiences in the commercial world increases, there
is a need to provide other alternative mechanisms for secure authentication. In
this paper, we analyze a few proposed authentication systems and reached a
conclusion that a multidimensional approach to authentication is needed to
address the granular nature of authentication and authorization needs of a
commercial virtual reality applications in the commercial world.
【2】 Bayesian Neural Networks for Reversible Steganography
标题：用于可逆隐写的贝叶斯神经网络
链接：https://arxiv.org/abs/2201.02478
摘要：Recent advances in deep learning have led to a paradigm shift in reversible
steganography. A fundamental pillar of reversible steganography is predictive
modelling which can be realised via deep neural networks. However, non-trivial
errors exist in inferences about some out-of-distribution and noisy data. In
view of this issue, we propose to consider uncertainty in predictive models
based upon a theoretical framework of Bayesian deep learning. Bayesian neural
networks can be regarded as self-aware machinery; that is, a machine that knows
its own limitations. To quantify uncertainty, we approximate the posterior
predictive distribution through Monte Carlo sampling with stochastic forward
passes. We further show that predictive uncertainty can be disentangled into
aleatoric and epistemic uncertainties and these quantities can be learnt in an
unsupervised manner. Experimental results demonstrate an improvement delivered
by Bayesian uncertainty analysis upon steganographic capacity-distortion
performance.
【3】 Unwinding Rotations Improves User Comfort with Immersive Telepresence Robots
标题：使用身临其境的网真机器人，展开旋转可提高用户舒适度
链接：https://arxiv.org/abs/2201.02392
备注：Accepted for publication in HRI (Int. Conf. on Human-Robot Interaction) 2022
摘要：We propose unwinding the rotations experienced by the user of an immersive
telepresence robot to improve comfort and reduce VR sickness of the user. By
immersive telepresence we refer to a situation where a 360\textdegree~camera on
top of a mobile robot is streaming video and audio into a head-mounted display
worn by a remote user possibly far away. Thus, it enables the user to be
present at the robot's location, look around by turning the head and
communicate with people near the robot. By unwinding the rotations of the
camera frame, the user's viewpoint is not changed when the robot rotates. The
user can change her viewpoint only by physically rotating in her local setting;
as visual rotation without the corresponding vestibular stimulation is a major
source of VR sickness, physical rotation by the user is expected to reduce VR
sickness. We implemented unwinding the rotations for a simulated robot
traversing a virtual environment and ran a user study (N=34) comparing
unwinding rotations to user's viewpoint turning when the robot turns. Our
results show that the users found unwound rotations more preferable and
comfortable and that it reduced their level of VR sickness. We also present
further results about the users' path integration capabilities, viewing
directions, and subjective observations of the robot's speed and distances to
simulated people and objects.
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