Most image analysis techniques are based upon low level descriptions of the data. It is
important that the chosen representation is able to discriminate as much as possible among …

This work tackles the segmentation of apparent-motion from a bottom-up perspective. When
no information is available to build prior high-level models, the only alternative are bottom …

Motion estimation methods can be broadly classified as being spatiotemporal or frequency
domain in nature. The Gabor representation is an analysis framework providing localized …

We define a visual pattern as an image feature with frequency components in a range of
bands that are aligned in phase. A technique to partition an image into its visual patterns …

Most existing object segmentation algorithms suffer from a so-called under-segmentation
problem, where parts of the segmented object are missing and holes often occur inside the …

Many seismic attributes today reveal fault and fracture patterns. However, these fault
attributes often suffer from noise or artifacts in the input data, resulting in data that is not high …

This paper deals with the problem of low level representation of 3D image contents. The
presented solution makes use of multiresolution techniques to recover the so-called visual …

In this paper, a new methodology for optical flow estimation that is able to represent multiple
motions is presented. To separate motions at the same location, a new frequency-domain …

In this paper we propose a technique for the decomposition of a 3D image into a set of low
level patterns associated to phase congruency, which we call visual patterns. Those patterns …

Motion estimation by means of spatio-temporal energy filters–velocity tuned filters–is known
to be robust to noise and aliasing and to allow an easy treatment of the aperture problem. In …