Anzeige
Erschienen in:
2008 | OriginalPaper | Buchkapitel
Background Subtraction Based on Local Orientation Histogram
verfasst von : DongHeon Jang, XiangHua Jin, YongJun Choi, TaeYong Kim
Erschienen in: Computer-Human Interaction
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Background Subtraction is an important preprocessing step for extracting the features of tracking objects in the vision-based HCI system. In this paper, the orientation histogram between the foreground image and the background image is compared to extract the foreground probability in the local area. The orientation histogram-based method is partially robust against illumination change and small moving objects in background. There are two major drawbacks of using histograms which are quantization errors in histogram binning and slow computation speed. With Gaussian binning and integral histogram, we present the recursive partitioning method that gives false detection suppression and fast computation speed.