Mean field theory-based motion estimation in the Laguerre Gauss domain

Marco Carli; Emanuele de Santis; Giovanni Iacovitti; Alessandro Neri

doi:10.1117/12.476606

7 May 2003 Mean field theory-based motion estimation in the Lagurerre Gauss domain

Marco Carli, Emanuele de Santis, Giovanni Iacovitti, Alessandro Neri

Proceedings Volume 5022, Image and Video Communications and Processing 2003; (2003) https://doi.org/10.1117/12.476606
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

In this paper the motion estimation between two consecutive color frames is analyzed by means of the Laguerre Gauss (LG) Wavelet Transform and the Mean Field theory. This contribution extends some previous work of the authors in this field. By decomposing the frames using the LG functions, a local image representation is obtained; using the self-steerability property of the LG it is possible to design a maximum likelihood estimation procedure to identify both the displacement and the rotation fields. To regularize the motion field taking in account the possible occlusions, the mean field theory has been used.

Citation Download Citation

Marco Carli, Emanuele de Santis, Giovanni Iacovitti, and Alessandro Neri "Mean field theory-based motion estimation in the Lagurerre Gauss domain", Proc. SPIE 5022, Image and Video Communications and Processing 2003, (7 May 2003); https://doi.org/10.1117/12.476606

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