Improved Video Segmentation by Adaptive Combination of Depth Keying and Mixture-of-Gaussians

  • Ingo Schiller
  • Reinhard Koch
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6688)

Abstract

Video segmentation or matting, the separation of foreground objects from background in video sequences, is a demanding task and is needed for a broad range of applications. The most widespread method for video segmentation is chroma-keying using a known background color for which a controlled environment is required. Recently a different method of keying fore-and background has been proposed in which the chroma-keying is replaced by depth-keying using a Time-of-Flight (ToF) camera. The current ToF-cameras suffer from noise and low resolution sensors, which results in unsatisfying segmentation results. We propose to combine the segmentation of dynamic objects in depth with a segmentation in the color domain using adaptive background models. We weight the two measures depending on the actual depth values using either the variance of the depth images of the ToF-camera or the amplitude image of the ToF-camera as reliability measure. We show that both methods significantly improve the segmentation results.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ingo Schiller
    • 1
  • Reinhard Koch
    • 1
  1. 1.Multimedia Information Processing (MIP) Institute of Computer ScienceUniversity of KielGermany

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