解耦光反射与瞳孔扩张测量视频中的情绪唤醒

Pallavi Raiturkar, A. Kleinsmith, A. Keil, Arunava Banerjee, Eakta Jain
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引用次数: 18

摘要

由于视频摘要、搜索相似视频和向用户推荐视频等应用,预测视频的精彩部分是一个广泛相关的问题。研究人员建议使用瞳孔扩张等生理指标来衡量情绪唤醒。用瞳孔测量情绪唤起的关键问题是瞳孔对亮度变化的反应。我们提出了一个瞳孔光反射的线性模型,仅基于入射光强度来预测观看者的瞳孔直径。瞳孔直径测量值与模型预测值之间的残差是由与该场景相对应的情绪唤醒引起的。我们评估了这种方法的有效性分解瞳孔光反射的视频摘要的特定应用。残差被转换成视频每一帧的兴奋度分数。我们展示了各种视频的结果,并与三个独立编码器报告的地面事实进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decoupling light reflex from pupillary dilation to measure emotional arousal in videos
Predicting the exciting portions of a video is a widely relevant problem because of applications such as video summarization, searching for similar videos, and recommending videos to users. Researchers have proposed the use of physiological indices such as pupillary dilation as a measure of emotional arousal. The key problem with using the pupil to measure emotional arousal is accounting for pupillary response to brightness changes. We propose a linear model of pupillary light reflex to predict the pupil diameter of a viewer based only on incident light intensity. The residual between the measured pupillary diameter and the model prediction is attributed to the emotional arousal corresponding to that scene. We evaluate the effectiveness of this method of factoring out pupillary light reflex for the particular application of video summarization. The residual is converted into an exciting-ness score for each frame of a video. We show results on a variety of videos, and compare against ground truth as reported by three independent coders.
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