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Edge-based 3-D camera motion estimation with application to video coding.

A Zakhor1, F Lari

  • 1California Univ., Berkeley, CA.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1993
PubMed
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New algorithms model camera motion in video using edge matching. These methods offer performance similar to block matching but with significantly lower computational complexity for zoom, pan, rotation, and translation.

Area of Science:

  • Computer Vision
  • Image Processing
  • Video Analysis

Background:

  • Accurate modeling of camera motion is crucial for video compression and analysis.
  • Existing methods like block matching can be computationally intensive.

Purpose of the Study:

  • To propose novel algorithms for modeling camera motion in video sequences.
  • To offer efficient alternatives to traditional motion estimation techniques.

Main Methods:

  • Two classes of algorithms are presented: one for non-translational motion (zoom, pan, rotation) and a more general one for translational and rotational motion.
  • Both algorithms utilize binary matching of edges in successive frames for motion estimation.
  • The generalized algorithm employs seven parameters and requires a depth map.

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Main Results:

  • The proposed edge-matching algorithms achieve rate-distortion performance comparable to block matching.
  • A significant reduction in computational complexity is demonstrated compared to block matching.

Conclusions:

  • Edge-based motion modeling provides an efficient approach for video sequence analysis.
  • These algorithms offer a viable trade-off between performance and computational cost.