Anomaly Foreground Detection through Background Learning in Video Surveillance

作者: Cheng-Yuan Tang , Yi-Leh Wu , Shih-Pin Chao , Wen-Chao Chen , Pan-Lan Chen

DOI: 10.1007/978-3-642-00909-9_41

关键词:

摘要: We present a new set of rapid detection background subtraction algorithms using codebooks to established Background Model (BG Model) and the concept Color originally proposed by [6]. The methods do not require prior learning, as in [6], can create an instant BG training with learning mechanism. Our also turn latter coming but stationary foreground objects gradually background, which are more adaptive actual environments. use absorb sudden camera movements caused show that effective efficient video surveillance applications.

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