Affiliation:
1. Department of Architecture, Chungbuk National University, Cheongju 28644, Republic of Korea
2. Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea
3. Institute of Construction and Environmental Engineering, Seoul National University, Seoul 08826, Republic of Korea
Abstract
The Bukchon area in Seoul boasts a high density of Hanok, the traditional Korean architecture representing the region. Because the Hanok facade plays a vital role in the streetscape formation, we must record it in terms of social, cultural, historical, artistic, and scenic values. However, recording the facade of an existing Hanok building through drawing or image information is time consuming and labor intensive, and therefore costly. Further, its digital conversion is inherently difficult. This study proposes the use of deep learning to identify the form elements that comprise the Hanok facade. Three-dimensional modeling was performed on 405 well-preserved Hanok facades in the region, and 2808 items of image data were created under similar conditions and at differing angles. Labeling was performed on the shape elements of the Hanok facade, and a methodology was established to identify the facade elements using MASK R-CNN. The type of roof, windows, the lower part of the outer wall, and the design were identified with high accuracy.
Subject
Nature and Landscape Conservation,Ecology,Global and Planetary Change
Reference50 articles.
1. Jacobs, J. (1961). Death and Life of Great American Cities, Random House.
2. Lynch, K. (1960). The Image of the City, The MIT Press.
3. Shon, D. (2018). Analysis of Traditional Urban Landscape Composition Using Data Mining. [Ph.D. Thesis, Seoul National University].
4. Kropf, K. (2018). The Handbook of Urban Morphology, John Wiley & Sons.
5. Dealing with incremental change: An application of urban morphology to design control;Hall;J. Urban Des.,1997