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首页> 外文会议>2011 IEEE International Conference on Systems, Man, and Cybernetics >Development of Kansei estimation models for the sense of presence in audio-visual content
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Development of Kansei estimation models for the sense of presence in audio-visual content

机译：开发用于视听内容中存在感的Kansei估计模型

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摘要

The term ‘presence’ is widely used to express the performances of audio-visual content and systems. Until now, many advanced audio-visual reproduction systems have been proposed to enable the perception of a higher degree of presence. Methodologies for evaluating the sense of presence derived from these systems also play an important role in the further evolution of audio-visual content and systems. This paper describes the construction of Kansei models which quantitatively evaluate the degree of presence in audio-visual content. Subjective evaluation experiments were conducted to investigate the relationship between the features of audio-visual content and the perceived sense of presence using 40 different types of audio-visual content. On the basis of evaluation scores and extracted audio-visual features, models were separately constructed for audio, visual and audio-visual content using neural networks. The performance tests of the constructed models demonstrated sufficient accuracy in estimating the sense of presence and statistically significant correlations between the model output and the subjective evaluation scores.
机译：“状态”一词被广泛用于表示视听内容和系统的性能。迄今为止，已经提出了许多先进的视听再现系统，以使人们能够感觉到更高的存在感。评估源自这些系统的存在感的方法在视听内容和系统的进一步发展中也起着重要作用。本文介绍了Kansei模型的构建，该模型定量评估了视听内容中的存在程度。进行了主观评估实验，以调查使用40种不同类型的视听内容的视听内容特征与感知到的存在感之间的关系。根据评估分数和提取的视听特征，使用神经网络分别构建了针对音频，视觉和视听内容的模型。所构建模型的性能测试证明，在估计存在感以及模型输出与主观评估得分之间的统计显着相关性方面具有足够的准确性。

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