A New Framework for Motion Estimation in Image Sequences Using Optimal Flow Control

  • Annette Stahl
  • Ole Morten Aamo
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 89)

Abstract

Application of tools from optimal flow control to the field of computer vision and image sequence processing, has recently led to a new and promising research direction. We present an approach to image motion estimation that uses an optimal flow control formulation subject to a physical constraint. Motion fields are forced to satisfy appropriate equations of motion. Although the framework presented is flexible with respect to selection of equations of motion, we employ the Burgers equation from fluid mechanics as physical prior knowledge in this study. To solve the resulting time-dependent optimisation problem we introduce an iterative method to uncouple the derived state and adjoint equations. We perform numerical experiments on synthetic and real image sequences and compare our results with other well-known methods to demonstrate performance of the optimal control formulation in determining image motion from video and image sequences. The results indicate improved performance.

Keywords

Optimal control Motion estimation Physical prior knowledge Optimisation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Annette Stahl
    • 1
  • Ole Morten Aamo
    • 1
  1. 1.Department of Engineering CyberneticsNorwegian University of Science and Technology (NTNU)TrondheimNorway

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