Detection of moving objects using incremental connectivity outlier factor algorithm

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 space. As the feature space, we use representation of videos by spatial-temporal blocks combined with principal component analysis for dimensionality reduction. Experimental evaluation of the proposed approach on a variety of test videos, including PETS repository, demonstrates its applicability and robustness on the choice of parameters.