Abstract
The classical problem of motion (or velocity field, or optical flow) estimation from a pair of consecutive frames of a video sequence is here approached in a context of Circular Harmonic Wavelet (CHW) 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 estimation procedure based on a bank of CHWs.
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