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딥 러닝과 마르코프 랜덤필드를 이용한 동영상 내 그림자 검출
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- Issue Date
- 2015-12
- Citation
- 멀티미디어학회논문지, v.18, no.12, pp.1432-1438
- ISSN
- 1229-7771
- Publisher
- 한국멀티미디어학회
- Language
- Korean
- Type
- Journal Article
- Abstract
- 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 Keywords
- Detection Method, Image segments, Markov Random Field, Moving shadow detection, Physical Properties, Surveillance system, Video sequences, Visual surveillance, deep learning(DL), state-of-The-Art