Silhouette extraction based on iterative spatio-temporal local color transformation and graph-cut segmentation

We propose an iterative scheme of spatio-temporal local color transformation of background and graph-cut segmentation for silhouette extraction. Given an initial background subtraction, spatio-temporal background color transformation is processed for fitting modeled background colors to input backgr...

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Bibliographic Details
Main Authors: Makihara, Y., Yagi, Y.
Format: Conference Proceeding
Language:eng ; jpn
Subjects:
Color
Gaussian distribution
Humans
Image segmentation
Layout
Legged locomotion
Lighting
Pixel
Testing
Yagi-Uda antennas
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Description
Summary:We propose an iterative scheme of spatio-temporal local color transformation of background and graph-cut segmentation for silhouette extraction. Given an initial background subtraction, spatio-temporal background color transformation is processed for fitting modeled background colors to input background ones under a different illumination condition. After foreground colors are modeled based on the fit background, spatio-temporal graph-cut algorithm is applied to acquire a foreground/background segmentation result. Because these two processes need well-segmented background and well-fit background each other, they are iterated in turn to obtain better silhouette extraction results. Silhouette extraction experiments for a walking human on a treadmill show the effectiveness of the proposed method.
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2008.4761121