Non-linear Bi-directional Prediction for Depth Coding

  • Authors:
  • Kwan-Jung Oh;Yo-Sung Ho

  • Affiliations:
  • Gwangju Institute of Science and Technology (GIST), Gwangju, Korea 500-712;Gwangju Institute of Science and Technology (GIST), Gwangju, Korea 500-712

  • Venue:
  • PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
  • Year:
  • 2009
  • Plenoptic sampling

    Proceedings of the 27th annual conference on Computer graphics and interactive techniques

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Abstract

A depth image represents a relative distance from a camera to an object in the three-dimensional (3-D) space and it is widely used as 3-D information in computer vision and computer graphics. Generally, the depth is represented as an image format and it is uniformly quantized in the disparity/intensity domain whereas it is non-uniformly quantized in the depth domain. Thus, the conventional bi-prediction applied in the disparity/intensity domain does not catch up the value for the linearly moving object. To solve this problem, we propose a non-linear bi-directional prediction for depth coding. Experimental results demonstrate that the proposed non-linear bi-directional prediction method achieves by 0.68 dB of the PSNR gain over the conventional method when the hierarchical-B picture coding is used.