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An Estimation Theoretic Perspective on Image Processing and the Calculation of Optical Flow

  • T. M. Chin
  • M. R. Luettgen
  • W. C. Karl
  • A. S. Willsky
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 220)

Abstract

Many problems of image processing and image sequence analysis involve both great computational complexity and the accommodation of noise and uncertainty through the indirect observation of quantities of interest. In this chapter we describe several aspects of an estimation theoretic approach to such problems. The vehicle for our development is the estimation of the apparent velocity field of a sequence of images. This apparent velocity field, known as the optical flow, appears as an important quantity in both the qualitative and quantitative analysis of image sequences. For example, knowledge of the optical flow is used in the detection of object boundaries and the segmentation of visual scenes [1, 2], the derivation of 3-D motion and structure [3, 4] and the compression of image sequences for efficient transmission [5, 6].

Keywords

Kalman Filter Optical Flow Prior Model Temporal Coherence Flow Estimate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1993

Authors and Affiliations

  • T. M. Chin
    • 1
  • M. R. Luettgen
    • 2
  • W. C. Karl
    • 2
  • A. S. Willsky
    • 2
  1. 1.RSMASU. of MiamiMiamiUSA
  2. 2.M.I.T.CambridgeUSA

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