Hee Jin Yoon, Ju Wan Kim, In Sung Jang, Byung-Dai Lee, Nam-Gi Kim, Journal of Internet Computing and Services, Vol. 20, No. 6, pp. 55-63, Dec. 2019
10.7472/jksii.2019.20.6.55, Full Text:  HTML
Keywords: shadow detection, deep-learning

Abstract

Recently, the use of real-world image data has been increasing to express realistic virtual environments in various application fields such as education, manufacturing, and construction. In particular, with increasing interest in digital twins like smart cities, realistic 3D urban models are being built using real-world images, such as aerial images. However, the captured aerial image includes shadows from the sun, and the 3D city model including the shadows has a problem of distorting and expressing information to the user. Many studies have been conducted to remove the shadow, but it is recognized as a challenging problem that is still difficult to solve. In this paper, we construct a virtual environment dataset including the height map of buildings using 3D spatial information provided by VWorld, and We propose a new shadow detection method using height map and deep learning. According to the experimental results, We can observed that the shadow detection error rate is reduced when using the height map.

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