2025年度 人工知能学会全国大会（第39回）
2025年5月27日〜5月30日大阪国際会議場＋オンライン
2025年度 人工知能学会全国大会（第39回）
2025年5月27日〜5月30日大阪国際会議場＋オンライン
[2K4-IS-1a-05]Location Awareness Google Street Image Retouching with Seasonal Changes
〇Chiau Wei Huang1, Ying Yu Chen1, Hao Ming Hung1, Hsiao Kuang Wu2, Lieu Hen Chen1(1. National Chi Nan University, Taiwan, 2. National Central University, Taiwan)
Streetscape, which represents the characteristics of a city, serves as a canvas that reflects the cultural essence and the emotional connection of its residents. Among its elements, street trees, in particular, illustrate the cyclical rhythm of nature and time through their seasonal changing appearances. In this paper, we propose a location aware system which enables users to experience the seasonal growth stages of street trees within the images of Google Street View. Our system integrates deep learning, computer graphics, and web data mining technologies. Tree images captured from Google MAP are dynamically retouched based on their GPS information and our database, which has web-crawled daily YouTube live camera data since 2021. The experimental results shown that our method can generate vivid, engaging, and dynamic images of street trees that align with the local natural and environmental conditions, therefore successfully enhancing users' experience and perception of seasonal changes in the street images.