Markovian motion field regularization based on the Gauss-Laguerre transform

Marco Carli; Giovanni Jacovitti; Alessandro Neri

doi:10.1117/12.411814

29 December 2000 Markovian motion field regularization based on the Gauss-Laguerre transform

Marco Carli, Giovanni Jacovitti, Alessandro Neri

Proceedings Volume 4310, Visual Communications and Image Processing 2001; (2000) https://doi.org/10.1117/12.411814
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

In this paper we address the classical problem of estimating, from a pair of consecutive frames of a video sequence, the motion (or velocity field, or optical flow) produced by planar translations and rotations, in the context of the Gauss- Laguerre Transform (GLT) theory. This contribution extends some previous works of the authors on wavelet based Optimum Scale-Orientation Independent Pattern Recognition. In particular here we make use of an orthogonal system of Laguerre-Gauss wavelets. Each wavelet represents the image by translated, dilated and rotated versions of a complex waveform whereas, for a fixed resolution, this expansion provides a local representation of the image around any point. In addition each waveform is self-steerable, i.e. it rotates by simple multiplication with a complex factor. These properties allow to derive an iterative joint translation and rotation field Maximum Likelihood (ML) estimation procedure based on a bank of CHWs. In this contribution the coarse estimate obtained by the memoryless, point wise, ML estimator is refined by resorting to a compound Markovian model that takes into account the spatial continuity of the motion field associated to a single object, by heavily penalizing abrupt changes in the motion intensity and direction not located in correspondence of intensity discontinuities (i.e. mostly object boundaries).

Citation Download Citation

Marco Carli, Giovanni Jacovitti, and Alessandro Neri "Markovian motion field regularization based on the Gauss-Laguerre transform", Proc. SPIE 4310, Visual Communications and Image Processing 2001, (29 December 2000); https://doi.org/10.1117/12.411814

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