In this paper, we present an algorithm for aligning and matching unlabeled sets of points and a method for building a statistical model composed of a mean observation and associated variability. This model is used to solve the cephalometric problem. The main idea of this paper consists in using a dual step strategy: estimate the pose and then the correspondence alternatively. Correspondence bei...

Template estimation plays a crucial role in computational anatomy since it provides reference frames for performing statistical analysis of the underlying anatomical population variability. While building models for template estimation, variability in sites and image acquisition protocols need to be accounted for. To account for such variability, we propose a generative template estimation mode...

In this work the use of statistical techniques will be approached for segmentation of SAR images, with the purpose of ship detection, being used RADARSAT images of the Brazilian coast. As described in Rocha et al (2001) and Rocha and Stech (2003), a specific software for ship detection was developed where, based on Eldhuset (1996), Vachon et al (1997), Oliver and Quegan (1998), Zaart et al (199...

An important problem in the use of density estimation for data analysis is whether or not observed features, such as bumps are “really there”, as opposed to being artifacts of the natural sampling variability. Here we propose a solution to this problem, in the challenging two dimensional case, using the graphical technique of Signi...cance in Scale Space. Color and dynamic graphics form an impo...

Dynamic Time Warping (DTW) is commonly used in gesture recognition tasks in order to tackle the temporal length variability of gestures. In the DTW framework, a set of gesture patterns are compared one by one to a maybe infinite test sequence, and a query gesture category is recognized if a warping cost inferior to a given value is found within the test sequence. Nevertheless, either taking one...

One of the fundamental challenges of human action recognition is accounting for the variability that arises during video capturing. For a specific action class, the 2D observations of different instances might be extremely different due to varying viewpoint when the sequences are captured by moving cameras. The situation is even worse if the actions are executed at different rates. In this pape...

We lay the ground for extending Dirichlet Processes based clustering and factor models to explicitly include variability as a function of time (or other known covariates) by integrating a Dependent Dirichlet Processes into existing hierarchical topic models. Time-Varying Topic Models using Dependent Dirichlet Processes Nathan Srebro Sam Roweis Dept. of Computer Science, University of Toronto, C...

At the heart of statistics lie the ideas of statistical inference. Methods of statistical inference enable the investigator to argue from the particular observations in a sample to the general case. In contrast to logical deductions made from the general case to the specific case, a statistical inference can sometimes be incorrect. Nevertheless, one of the great intellectual advances of the twe...

Recent experience can influence judgments in a wide range of tasks, from reporting physical properties of stimuli to grading papers to evaluating movies. In this work, we analyze data from a task involving a series of judgments of pain (discomfort) made by participants who were asked to place their hands in a bowl of water of varying temperature. Although trials in this task were separated by a...