Open AccessForeground extraction based on anomaly detection
Author(s) -
Wang Yong,
Wang Dianhong
Publication year - 2014
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2013.3412
Subject(s) - anomaly detection , pixel , artificial intelligence , anomaly (physics) , pattern recognition (psychology) , computer science , series (stratigraphy) , markov chain , computer vision , physics , machine learning , biology , condensed matter physics , paleontology
A robust method to detect foreground regions in video sequences is presented. For each pixel, the time series of pixel intensity is represented as symbol sequences that are trained and modelled using the Markov model to obtain the anomaly detection threshold. The foreground extraction is performed by comparing the anomaly transition probability of each pixel and its detection threshold. The experimental results demonstrate that the proposed method outperforms the traditional methods.