9 November 2017 RGB-D foreground extraction from a moving camera using nonlinear pixel classification
Naveed Ahmed, Imran Junejo
Author Affiliations +
Abstract
We propose a foreground extraction method from a freely moving RGB-D video camera that uses a nonlinear optimization function to classify pixels in every frame as either foreground or background. The method starts with extracting sparse features in every frame. These features are then matched to create a nonlinear optimization function that is used to label each pixel in the depth image as either foreground or background. Finally, the inverse mapping from depth to RGB data is used to extract the foreground from the RGB image. Our results show that even in the presence of high camera motion, it is possible to reliably extract the foreground from the RGB-D video data captured from a freely moving camera.
© 2017 SPIE and IS&T 1017-9909/2017/$25.00 © 2017 SPIE and IS&T
Naveed Ahmed and Imran Junejo "RGB-D foreground extraction from a moving camera using nonlinear pixel classification," Journal of Electronic Imaging 26(6), 063009 (9 November 2017). https://doi.org/10.1117/1.JEI.26.6.063009
Received: 20 May 2017; Accepted: 19 October 2017; Published: 9 November 2017
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KEYWORDS
Cameras

RGB color model

Video

Feature extraction

Clouds

Data acquisition

Associative arrays

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