Application of AR virtual implantation technology based on deep learning and emotional technology in the creation of interactive picture books

Si-yu Liu, Peng Peng, Lei Cao
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Abstract

In recent years, the field of deep learning has flourished, not only breaking through many difficult problems that are difficult to be solved by traditional algorithms but also bursting with greater vitality when combined with other fields. For example, product emotional design based on deep learning can integrate users' emotional needs into the actual product design. In this paper, we aim to use deep learning and affective technology in the creation of AR interactive picture books to transform the reading process from static to dynamic, enrich visual stimulation, and increase the fun and interactivity of reading. In this paper, based on the three-level theoretical model of emotion, the emotion labeling results are input to a deep neural network for learning, to establish an emotion-based recognition model for picture book images. The results show that the model can well analyze the emotion of images in AR picture books, and the accuracy of prediction is a big improvement compared with traditional machine recognition algorithms. The application of AR virtual implantation technology in interactive picture books on the market is often just a marketing gimmick while combining deep learning and emotional technology can better create diverse interactive picture books to meet children's emotional reading needs, enhance reading engagement, and stimulate children's creativity.
基于深度学习和情感技术的AR虚拟植入技术在互动绘本创作中的应用
近年来,深度学习领域蓬勃发展,不仅突破了许多传统算法难以解决的难题,而且与其他领域相结合,焕发出更大的生命力。例如,基于深度学习的产品情感设计可以将用户的情感需求融入到实际的产品设计中。本文旨在将深度学习和情感技术应用于AR互动绘本的创作中,将阅读过程从静态转变为动态,丰富视觉刺激,增加阅读的趣味性和互动性。本文基于情感的三层理论模型,将情感标注结果输入深度神经网络进行学习,建立基于情感的绘本图像识别模型。结果表明,该模型可以很好地分析AR绘本中图像的情感,预测精度与传统的机器识别算法相比有较大提高。市场上将AR虚拟植入技术应用于互动绘本往往只是一种营销噱头,而将深度学习与情感技术相结合,可以更好地创造出多样化的互动绘本,满足儿童的情感阅读需求,增强阅读参与度,激发儿童的创造力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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