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Published in:
2018 | OriginalPaper | Chapter
Foreground Background Segmentation in Front of Changing Footage on a Video Screen
Authors : Gianni Allebosch, Maarten Slembrouck, Sanne Roegiers, Hiêp Quang Luong, Peter Veelaert, Wilfried Philips
Published in: Advanced Concepts for Intelligent Vision Systems
Publisher: Springer International Publishing
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Abstract
In this paper, a robust approach for detecting foreground objects moving in front of a video screen is presented. The proposed method constructs a background model for every image shown on the screen, assuming these images are known up to an appearance transformation. This transformation is guided by a color mapping function, constructed in the beginning of the sequence. The foreground object is then segmented at runtime by comparing the input from the camera with a color mapped representation of the background image, by analysing both direct color and edge feature differences. The method is tested on challenging sequences, where the background screen displays photo-realistic videos. It is shown that the proposed method is able to produce accurate foreground masks, with obtained \(F_1\)-scores ranging from 85.61% to 90.74% on our dataset.