A Study on the Factors Affecting Audio-Video Subjective Experience in Virtual Reality Environments

Zhao, Junzhe; Zhang, Bo; Yan, Zhaoyu; Wang, Jing; Fei, Zesong

doi:10.1109/icvrv.2017.00070

Cited by 6 publications

(3 citation statements)

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“…Since visual effects (including avatars and their positions in the virtual space) and audio effects are essential parts of a virtual reality user experience, their synchronization is a critical feature of a VRE. It takes two forms, i.e., time synchronization and spatial synchronization of audio and video [69]. In the case of time synchronization, the term suggests that even 0.1 second of delay of one over the other has a serious negative effect in the user's experience [70].…”

Section: Time and Spatial Synchronizationmentioning

confidence: 99%

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Collaboration in Virtual Reality: Survey and Perspectives

Xanthidou

Aburumman

Ben-Abdallah

2023

Preprint

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The application of Virtual Reality Environments (VRE) has been gaining momentum as a relatively new tool to assist with mitigating various difficulties including abstractness of concepts, lack of user engagement, perception of disconnection from other users. A VRE may offer both synchronous and asynchronous experiences, in addition to an immersive environment which promotes users’ engagement. Past research has shown that, in general, VRE do improve the experiences they try to enhance in many aspects of human activity. Terms like immersiveness and 3D representation of real life objects and environments are, as it appears, the two most obvious positive effects of Virtual Reality (VR) applications. However, despite these benefits it does not come without challenges. The main three concepts/challenges are the spatial design, the collaboration interaction between its members and the VRE, and the audio and video fidelity. Each of the three includes a number of other components that should be addressed for the total experience to be fine-tuned. These include mutual embodiment and shared perspectives, teleportation, gestural interaction, symmetric and asymmetric collaboration, physical and virtual co-location, inventory, and time and spatial synchronization. This paper comprises a survey of the literature, that identifies and explains the features introduced and the challenges involved with the VREs, and furthermore provides various interesting future research directions.

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Section: Time and Spatial Synchronizationmentioning

confidence: 99%

“…must also match the positions of each other. For example, the audio should change its intensity as the user's avatar is moving closer to or away from a particular object emanating that audio [69].…”

Section: Time and Spatial Synchronizationmentioning

confidence: 99%

Collaboration in Virtual Reality: Survey and Perspectives

Xanthidou

Aburumman

Ben-Abdallah

2023

Preprint

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“…vision, to be unacceptable. Zhao et al [2] showed, through a human study, that humans find A/V sync errors to be even more detrimental to subjective experience than video impairments or audio impairments for virtual reality environments. Detecting such errors in A/V sync is a challenging task, but developing automated algorithms for it is vital for video-on-demand and livestreaming services to operate at scale.…”

Section: Introductionmentioning

confidence: 99%

Detection of Audio-Video Synchronization Errors Via Event Detection

Ebenezer¹,

Wu²,

Wei³

et al. 2021

Preprint

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We present a new method and a large-scale database to detect audio-video synchronization(A/V sync) errors in tennis videos. A deep network is trained to detect the visual signature of the tennis ball being hit by the racquet in the video stream. Another deep network is trained to detect the auditory signature of the same event in the audio stream. During evaluation, the audio stream is searched by the audio network for the audio event of the ball being hit. If the event is found in audio, the neighboring interval in video is searched for the corresponding visual signature. If the event is not found in the video stream but is found in the audio stream, A/V sync error is flagged. We developed a large-scaled database of 504,300 frames from 6 hours of videos of tennis events, simulated A/V sync errors, and found our method achieves high accuracy on the task.

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