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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Real-time foreground segmentation via range and color imaging
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Ryan Crabb, University of California at Santa Cruz, USA
Colin Tracey, Canesta, Inc. Sunnyvale, CA, USA
Akshaya Puranik, Canesta, Inc. Sunnyvale, CA, USA
James Davis, University of California at Santa Cruz, USA
This paper describes a real-time method for foreground/background segmentation of a color video sequence based primarily on range data of a time-of-flight sensor. This method uses depth information of a TOF-sensor paired with a high resolution color video camera to efficiently segment foreground from background in a two-step process. First a trimap is produced using only range data: areas are located in each frame that have a high probability of being background or foreground, respectively. Pixels which cannot be definitively classified as foreground or background, typically about 1–2% of the frame, are assigned alpha-matte values using a cross bilateral filtering, applied directly to an estimate of the alpha-matte.
Citation:
Ryan Crabb, Colin Tracey, Akshaya Puranik, James Davis, "Real-time foreground segmentation via range and color imaging," cvprw, pp.1-5, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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