Nebojsa Pejcic

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Outlier detection has recently become an important problem in many industrial and financial applications. Often, outliers have to be detected from data streams that continuously arrive from data sources. Incremental outlier detection algorithms, aimed at detecting outliers as soon as they appear in a database, have recently become emerging research field.(More)
In this paper, we describe a technique for detection of moving objects in RGB and infra-red (IR) videos. The technique is based on novel incremental connectivity-based outlier factor (IncCOF). The main idea of the proposed approach is to detect moving blocks as outliers---objects dissimilar to objects in their vicinity--within a properly defined feature(More)
Recent research in motion detection has shown that various outlier detection methods could be used for efficient detection of small moving targets. These algorithms detect moving objects as outliers in a properly defined attribute space, where outlier is defined as an object distinct from the objects in its neighborhood. In this paper, we compare the(More)
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