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초록
Recently, with personal information being increasingly used in several applications, its leakage and resulting damage have become a relevant concern. In video data, only people consenting to the collection of personal data are to be identified, and other people should be de-identified. In current automatic de-identification, not all objects are identified, and de-identification of only recognized objects is performed manually using video editor tools. Therefore, in this study, face/object-detection-based automatic selective de-identification was conducted through artificial intelligence technology to identify approved objects and de-identify remaining objects. Thus, selective protection can be automatically performed while ensuring the usability and stability of personal information.
키워드
- 제목
- Vision AI-Based Automatic Selective De-Identification
- 저자
- 김대진; 전윤걸
- 발행일
- 2023-04
- 유형
- Y
- 저널명
- 디지털콘텐츠학회논문지
- 권
- 24
- 호
- 4
- 페이지
- 725 ~ 734
- 언어
- ENG
- 출판사
- 한국디지털콘텐츠학회
- 발행국가
- 대한민국
- 분량
- 10 페이지
- ISSN
- E 2287-738X
P 1598-2009