Open Access

An Algorithm for Motion Parameter Direct Estimate

  • Roberto Caldelli1Email author,
  • Franco Bartolini1 and
  • Vittorio Romagnoli1
EURASIP Journal on Advances in Signal Processing20042004:349123

Received: 29 January 2003

Published: 15 June 2004


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.


motion parameter estimationMAP criterionMarkov random fieldsiterated conditional modemotion models

Authors’ Affiliations

Dipartimento di Elettronica e Telecomunicazioni, Università di Firenze


© Caldelli et al. 2004