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Audio-Visual Perception of Omnidirectional Video for Virtual Reality Applications

机译:虚拟现实应用全向视频的视听感知

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Ambisonics, which constructs a sound distribution over the full viewing sphere, improves immersive experience in omnidirectional video (ODV) by enabling observers to perceive the sound directions. Thus, human attention could be guided by audio and visual stimuli simultaneously. Numerous datasets have been proposed to investigate human visual attention by collecting eye fixations of observers navigating ODV with head-mounted displays (HMD). However, there is no such dataset analyzing the impact of audio information. In this paper, we establish a new audio-visual attention dataset for ODV with mute, mono, and ambisonics. The user behavior including visual attention corresponding to sound source locations, viewing navigation congruence between observers and fixations distributions in these three audio modalities is studied based on video and audio content. From our statistical analysis, we preliminarily found that, compared to only perceiving visual cues, perceiving visual cues with salient object sound (i.e., human voice, siren of ambulance) could draw more visual attention to the objects making sound and guide viewing behaviour when such objects are not in the current field of view. The more in-depth interactive effects between audio and visual cues in mute, mono and ambisonics still require further comprehensive study. The dataset and developed testbed in this initial work will be publicly available with the paper to foster future research on audio-visual attention for ODV.
机译:Ambisonics构建了整个观看范围内的声音分布,通过使观察者能够感知声音的方向,从而改善了全向视频(ODV)的沉浸式体验。因此,人们的注意力可以同时受到音频和视觉刺激的引导。已经提出了许多数据集,以通过收集使用头戴式显示器(HMD)导航ODV的观察者的眼神来调查人类的视觉注意力。但是,没有这样的数据集可以分析音频信息的影响。在本文中,我们为带有静音,单声道和歧音的ODV建立了一个新的视听注意力数据集。基于视频和音频内容,研究了包括与声源位置相对应的视觉注意力,观察者之间的观看导航一致性以及这三种音频模态中的注视分布在内的用户行为。从我们的统计分析中,我们初步发现,与仅感知视觉线索相比,感知带有明显物体声音的视觉线索(例如,人声,救护车警笛声)可以将更多的视觉注意力吸引到发出声音的物体上,并在这种情况下引导观看行为对象不在当前视野中。静音,单声道和混音中音视频提示之间更深入的交互效果仍需要进一步的综合研究。该初始工作中的数据集和开发的测试平台将随该文件公开提供,以促进对ODV视听注意力的未来研究。

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