Game Audio Impacts on Players’ Visual Attention, Model Performance for Cloud Gaming

Morva Saaty, M. Hashemi
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引用次数: 1

Abstract

Cloud gaming (CG) is a new approach to deliver a high-quality gaming experience to gamers anywhere, anytime, and on any device. To achieve this goal, CG requires a high bandwidth, which is still a major challenge. Many existing research pieces have focused on modeling or predicting the players’ Visual Attention Map (VAM) and allocating bitrate accordingly. Although studies indicate that both modalities of audio and video influence human perception, a few studies considered audio impacts in the cloud-based attention models. This paper demonstrates that the audio features in video games change the players’ VAMs in various game scenarios. Our findings indicated that incorporating game audio improves the accuracy of the predicted attention maps by 13% on average compared to the previous VAMs generated based on visual saliency by Game Attention Model for CG. The audio impact is more evident in video games with fewer visual components or indicators on the screen.
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游戏音频对玩家视觉注意力的影响,云游戏模型性能
云游戏(CG)是一种向玩家提供高质量游戏体验的新方法,无论何时何地,在任何设备上。为了实现这一目标,CG需要高带宽,这仍然是一个重大挑战。许多现有的研究都集中在建模或预测玩家的视觉注意地图(VAM)并相应地分配比特率。尽管研究表明音频和视频两种模式都影响人类感知,但少数研究在基于云的注意力模型中考虑了音频的影响。本文论证了电子游戏中的音频特征在不同的游戏场景下会改变玩家的VAMs。我们的研究结果表明,与之前由CG游戏注意力模型基于视觉显著性生成的VAMs相比,结合游戏音频可将预测注意力地图的准确性平均提高13%。在屏幕上的视觉组件或指示器较少的电子游戏中,音频影响更为明显。
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