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- 발행일
- 201512
- 출처
- 멀티미디어학회논문지, v.18 no.12, pp.1432-1438
- ISSN
- 1229-7771
- 출판사
- 한국멀티미디어학회
- 협약과제
- 15ZI2200, 대경권 지역산업연계 IT융합기술개발 및 산업계 지원사업, 정윤수
- 초록
- We present a methodology to detect moving shadows in video sequences, which is considered as a challenging and critical problem in the most visual surveillance systems since 1980s. While most previous moving shadow detection methods used hand-crafted features such as chromaticity, physical properties, geometry, or combination thereof, our method can automatically learn features to classify whether image segments are shadow or foreground by using a deep learning architecture. Furthermore, applying Markov Random Field enables our system to refine our shadow detection results to improve its performance.Our algorithm is applied to five different challenging datasets of moving shadow detection, and its performance is comparable to that of state-of-the-art approaches.
- KSP 제안 키워드
- Detection Method, Image segments, Markov Random Field, Moving shadow detection, Physical Properties, Surveillance system, deep learning(DL), state-of-The-Art, video sequences, visual surveillance