基于SNS照片颜色提取和情感分析的图片地图生成

Yuanyuan Wang
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引用次数: 0

摘要

近年来,许多SNS照片发布网站变得流行起来,许多用户分享各种景点的照片。另一方面,作为一种娱乐形式,海外旅游的目的排名靠前的是与放松和减压等情绪有关。以前基于情感的旅游景点推荐严重依赖文本数据进行情感分析。但是,他们没有利用旅游景点照片的特点。特别是色彩信息具有特定的形象和心理效应,利用色彩信息进行旅游信息推荐可以影响人们的感官和情感。例如,绿色提供心理效果,如放松和治疗。因此,在本研究中,我们着眼于心理和情感对颜色的影响,提出了一种从SNS照片中提取颜色信息,分析颜色的情感,然后将其与SNS照片的元数据相结合,从而生成图像地图的方法。通过在地图上绘制与目的地相匹配的旅游景点照片,用户可以直观地搜索到与自己的心情相关的旅游景点,比如放松或减压。此外,它还有望改善感官行为,比如为旅行选择颜色。最后,我们利用点信息和标签云开发了图形地图的可视化界面,并通过问卷调查验证了用户对图形地图可视化的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pictorial Map Generation based on Color Extraction and Sentiment Analysis using SNS Photos
In recent years, many SNS photo-posting sites have become popular, and many users share photos of various spots. On the other hand, the top ranking of the purpose of overseas travel as a form of entertainment is related to sentiment such as relaxation and stress reduction. Previous sentiment-based tourist spot recommendations relied heavily on textual data for sentiment analysis. However, they do not utilize the characteristics of photos showing tourist spots. In particular, color information has its specific image and psychological effects, and using this information in recommending tourist information can affect the senses and sentiments of people. For example, the green provides psychological effects, such as relaxation and healing. Therefore, in this work, we focus on the psychological and sentimental effects on colors and propose a method for generating a pictorial map by extracting color information from SNS photos, analyzing the sentiments of colors, and then combining them with the metadata of the SNS photos. It allows users to intuitively search for the desired spots when traveling for purposes related to their sentiments, such as relaxation or stress reduction, by mapping the photos of tourist spots that match their destinations on the map. Furthermore, it is expected to improve sensory behavior, such as choosing colors for a trip. Finally, we developed a visualization interface for the pictorial map using spot information and tag clouds, and we validated the usefulness of the pictorial map visualization by users through a questionnaire survey.
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