This paper extends 2D active shape models to 2D þ time by presenting a method for modeling and segmenting spatio-temporal shapes (ST-shapes). The modeling part consists of constructing a statistical model of ST-shape parameters. This model describes the principal modes of variation of the ST-shape in addition to constraints on the allowed variations. An active approach is used in segmentation w...

The mixture model is a commonly used approach for image segmentation. However, it doesn’t consider the spatial information. In order to overcome this disadvantage, several spatially constrained mixture models have been proposed. In this paper, these spatially constrained mixture models and their experimental results on synthetic and real world images are presented. These experimental results de...

The assumption of weak scattering is standard for the mathematical analysis of synthetic aperture radar (SAR), as it helps linearize the inverse problem via the first Born approximation and thus makes it amenable to solution. Yet it is not consistent with another common assumption, that the interrogating waves do not penetrate into the target material and get scattered off its surface only, whi...

We present a Bayesian approach for model-based classi"cation from unordered, attributed feature sets. A set of features is estimated from measured data and is matched with a set predicted for each candidate hypothesis using a feature model. Both extracted and predicted feature sets have uncertainty, and some features may not be present in one set or the other. Computation of the match likelihoo...

This paper extends 2D Active Shape Models to 2D+time by presenting a method for modelling and segmenting spatio-temporal shapes (ST-shapes). The modelling part consists of constructing a statistical model of ST-shape parameters. The model obtained describes the principal modes of variation of the ST-shape in addition to certain constraints on the allowed variations. An active approach is used i...

Motivation: The modeling and simulation of genetic regulatory networks have created the need for tools for model validation. The main challenges of model validation are the achievement of a match between the precision of model predictions and experimental data, as well as the efficient and reliable comparison of the predictions and observations. Results: We present an approach towards the valid...

shear-wave velocity ( ) is an important parameter used for site characterization in geotechnical engineering. however, dispersion curve inversion is challenging for most inversion methods due to its high non-linearity and mix-determined trait. in order to overcome these problems, in this study, a joint inversion strategy is proposed based on the particle swarm optimization (pso) algorithm. the ...

We propose a new probabilistic model for analyzing dynamic evolutions of relational data, such as additions, deletions and split & merge, of relation clusters like communities in social networks. Our proposed model abstracts observed timevarying object-object relationships into relationships between object clusters. We extend the infinite Hidden Markov model to follow dynamic and time-sensitive...

Shear-wave velocity ( ) is an important parameter used for site characterization in geotechnical engineering. However, dispersion curve inversion is challenging for most inversion methods due to its high non-linearity and mix-determined trait. In order to overcome these problems, in this study, a joint inversion strategy is proposed based on the particle swarm optimization (PSO) algorithm. The ...

Edge detection and edge enhancement techniques play an essential role in interpreting potential field data. This paper describes the application of various edge detection techniques to gravity data in order to delineate the edges of subsurface structures. The edge detection methods comprise analytic signal, total horizontal derivative (THDR), theta angle, tilt angle, hyperbolic of tilt angle (H...