Skip to main content

An Algorithm for Motion Parameter Direct Estimate

Abstract

Motion estimation in image sequences is undoubtedly one of the most studied research fields, given that motion estimation is a basic tool for disparate applications, ranging from video coding to pattern recognition. In this paper a new methodology which, by minimizing a specific potential function, directly determines for each image pixel the motion parameters of the object the pixel belongs to is presented. The approach is based on Markov random fields modelling, acting on a first-order neighborhood of each point and on a simple motion model that accounts for rotations and translations. Experimental results both on synthetic (noiseless and noisy) and real world sequences have been carried out and they demonstrate the good performance of the adopted technique. Furthermore a quantitative and qualitative comparison with other well-known approaches has confirmed the goodness of the proposed methodology.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Roberto Caldelli.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Caldelli, R., Bartolini, F. & Romagnoli, V. An Algorithm for Motion Parameter Direct Estimate. EURASIP J. Adv. Signal Process. 2004, 349123 (2004). https://doi.org/10.1155/S1110865704401012

Download citation

Keywords

  • motion parameter estimation
  • MAP criterion
  • Markov random fields
  • iterated conditional mode
  • motion models