Semi-automatic synthetic depth map generation for video using random walks

  • Authors:

  • Richard Rzeszutek;Raymond Phan;Dimitrios Androutsos

  • Affiliations:

  • Department of Electrical & Computer Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario, Canada, M5B 2K3;Department of Electrical & Computer Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario, Canada, M5B 2K3;Department of Electrical & Computer Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario, Canada, M5B 2K3

  • Venue:
  • ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
  • Year:
  • 2011

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Abstract

We present a method for easily generating depth maps from monoscopic (i.e. "2D") video footage in order to convert them into stereoscopic, or "3D", footage. Our method uses user-defined strokes for a number of keyframes in the original footage and interpolates between the keyframes to provide a sparse labelling for each frame. We then apply the Random Walks algorithm to the footage to provide depth estimates based on the input provided by the user. These depth maps can then be used to generate novel views through depth-based image rendering.