This paper presents a new model for optical ow based on the motion of planar regions plus local deformations. The approach exploits brightness information to organize and constrain the interpretation of the motion by using segmented regions of piecewise smooth brightness to hypothesize planar regions in the scene. Parametric ow models are tted to these regions in a two step process which rst co...

17 a similar reason, we did not nd the method of projection pursuit 5] in exploratory data analysis useful in this context. 4 Conclusions We described a method for inferring from the training data faithful but concise representations of the empirical class-conditional distributions. In doing this, we have abandoned many usual simplifying assumptions about the distributions: e.g. that they are s...

Population viability analysis (PVA) to forecast extinction risk is a commonly used tool in decision- and policy-making processes of governments and conservation organizations. A drawback to PVA is the high degree of uncertainty in these forecasts due to both population stochasticity and parameter estimation uncertainty. With sparse or noisy data, extinction probabilities frequently have 95% con...

‎In this study‎, ‎we investigate topological properties of fuzzy strong‎ b-metric spaces defined in [13]‎. ‎Firstly‎, ‎we prove Baire's theorem for‎ ‎these spaces‎. ‎Then we define the product of two fuzzy strong b-metric spaces‎ ‎defined with same continuous t-norms and show that $X_{1}times X_{2}$ is a‎ ‎complete fuzzy strong b-metric space if and only if $X_{1}$ and $X_{2}$ are‎ ‎complete fu...

This paper presents the work of the MMIS group done at ImageCLEF 2009. We submitted five different runs to the Photo Annotation task. These runs were based on two non-parametric density estimation models. The first one evaluates a set of visual features and proposes a better, weighted set of features. The second approach uses keyword correlation to compute semantic similarity measures using sev...

Abstract. Histograms are commonly used for representing summaries of observed data and they can be considered non parametric estimates of probability distributions. Symbolic Data Analysis formalized the concept of histogram symbolic variable, as a variable which allows to describe statistical units by histograms instead of single values. In this paper we present a linear regression model for mu...

This paper presents the Unanimous Improvement Ratio (UIR), a measure that allows to compare systems using two evaluation metrics without dependencies on relative metric weights. For clustering tasks, this kind of measure becomes necessary given the trade-off between precision and recall oriented metrics (e.g. Purity and Inverse Purity) which usually depends on a clustering threshold parameter s...

21 Object Matching 2 21.1 Various matching methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 21.2 Methods through localization/registration . . . . . . . . . . . . . . . . . . . . 2 21.3 Classification of matching methods . . . . . . . . . . . . . . . . . . . . . . . . 2 21.4 Problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 21.4.1 Distance ...

The use of mathematical models in the sciences often requires the estimation of unknown parameter values from data. Sloppiness provides information about the uncertainty of this task. In this paper, we develop a precise mathematical foundation for sloppiness and define rigorously its key concepts, such as ‘model manifold’, in relation to concepts of structural identifiability. We redefine slopp...

We introduce and test several novel approaches for periodicity detection in unevenlyspaced sparse datasets. Specifically, we examine five different kinds of periodicity metrics, which are based on non-parametric measures of serial dependence of the phase-folded data. We test the metrics through simulations in which we assess their performance in various situations, including various periodic si...