인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 중앙대학교 영상콘텐츠융합연구소 TECHART: Journal of Arts and Imaging Science TECHART: Journal of Arts and Imaging Science Vol.8 No.2
- 발행연도
- 2021.5
- 수록면
- 15 - 18 (4page)
- DOI
- 10.15323/techart.2021.5.8.2.15
이용수
초록· 키워드
In this paper, we propose a method of matting the background of photos, excluding human objects, using an improved BASNet featuring the convolutional block attention module (CBAM). Image matting is widely used in media art as a way to change background images to different settings, except for the desired objects. We added CBAM to BASNet to increase performance by maintaining its speed through end-to-end training. The proposed artwork consists of three steps. First, the improved BASNet is used to detect the area in the image and calculate the saliency and foreground maps. Second, the saliency map is resized through interpolation, and zero-padding is applied to match the size with the background image. Finally, the saturation calculation of the desired background and saliency map is performed, the saliency area is changed to black using thresholding, and the image and foreground map are saturated again. As a result, we can improve BASNet through our proposed method to better mat the background. The method presented can convey this richer visual beauty by providing a visual illusion through image matting without the use of a chroma key.
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목차
- Abstract
- 1. Introduction
- 2. Related work
- 3. Process
- 3. Experimental results
- 4. Conclusion
- References
참고문헌
참고문헌 신청최근 본 자료
UCI(KEPA) : I410-ECN-0101-2021-688-001727780
