In this paper new error measures to evaluate image features in 3D scenes are proposed and reviewed. The proposed error measures are designed to take into account feature shapes, and ground truth data can be easily estimated. As other approaches, they are not error-free and a quantitative evaluation is given according to the number of wrong matches and mismatches in order to assess their validity.

The combination of computational models and biophysical simulations can help to interpret an array of experimental data and contribute to the understanding, diagnosis and treatment of complex diseases such as cardiac arrhythmias. For this reason, three-dimensional (3D) cardiac computational modelling is currently a rising field of research. The advance of medical imaging technology over the las...

Five patients (four adults and one child) with clinically suspected myocardial perforation by temporary transvenous pacemakers were studied by real-time, two-dimensional echocardiography. In three patients, the catheters were visualized passing through the right ventricular apical wall with the tip located outside the cardiac border. In one patient the catheter perforated the atrioventricular s...

High dimensional engineered features have yielded high performance results on a variety of visual recognition tasks and attracted significant recent attention. Here, we examine the problem of expression recognition in static facial images. We first present a technique to build high dimensional, ∼60k features composed of dense Census transformed vectors based on locations defined by facial keypo...

Neither of the classical visual servoing approaches, position-based and image-based, are completely satisfactory. In position-based visual servoing the trajectory of the robot is well stated, but the approach suffers mainly from the image features going out of the visual field of the cameras. On the other hand, image-based visual servoing has been found generally satisfactory and robust in the ...

This paper introduces a new method to analyse the image texture and to index the image database. We present a new strategy to reduce the computational time to extract image features with high retrieval accuracy. We also propose a method to reduce the image feature dimension, so any robust indexing methods can be used. By weighting the extracted image features, a system may perceive the image co...

This thesis responds to the challenges of using a large number, such as thousands, of features in regression and classification problems. There are two situations where such high dimensional features arise. One is when high dimensional measurements are available, for example, gene expression data produced by microarray techniques. For computational or other reasons, people may select only a sma...

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is poorly understood. In a seminal paper, Bickel and Levina [Bernoulli 10 (2004) 989–1010] show that the Fisher discriminant performs poorly due to diverging spectra ...

Graphs are commonly used to encode relationships among entities, yet, their abstractness makes them incredibly difficult to analyze. Node-link diagrams are a popular method for drawing graphs. Classical techniques for the node-link diagrams include various layout methods that rely on derived information to position points, which often lack interactive exploration functionalities; and force-dire...

We studied the two-dimensional freezing transitions in monolayers of microgel colloidal spheres with short-ranged repulsions in video-microscopy experiments, and monolayers of hard disks, and Yukawa particles in simulations. These systems share two common features at the freezing points: (1) the bimodal distribution profile of the local orientational order parameter; (2) the two-body excess ent...