Abstract
In the applications of interior and architectural design, there are various tasks range from ensuring desired floor colors/textures plans, to deciding furnishing arrangement styles: all depending upon the choices of designers themselves. Thus in this modern era of artificial intelligence, computer vision based applications are very popular. Many research studies have been conducted to address different interior design applications using virtual reality technology. However, VR based applications do not provide a realistic experience to the user for interior design. Therefore in this study, we present an Augmented Reality (AR) based end-to-end systematic approach for interior design initialized by deep matting of an indoor scene. In our proposed application, the user has the authority to choose various colors/textures to change the interior of the region of interest in an indoor environment. Our proposed application has different modules working jointly for efficient interactive interior design. It allows the user to select its region of interest (wall or floor) and then give options to choose a color/texture to map on ROI for interior design experience. The final results of our proposed approach give realistic experience to the users as we estimate the global illumination changes on the ROI in our joint modules. Hence in this way, our presented interactive interior design application is user-friendly and works efficiently with realistic looking outputs.
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Acknowledgement
This study was supported by the BK21 Plus project (SW Human Resource Development Program for Supporting Smart Life) funded by the Ministry of Education, School of Computer Science and Engineering, Kyungpook National University, Korea (21A20131600005).
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Sultana, M., Kim, I.S., Jung, S.K. (2020). Deep Matting for AR Based Interior Design. In: Ohyama, W., Jung, S. (eds) Frontiers of Computer Vision. IW-FCV 2020. Communications in Computer and Information Science, vol 1212. Springer, Singapore. https://doi.org/10.1007/978-981-15-4818-5_3
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DOI: https://doi.org/10.1007/978-981-15-4818-5_3
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