Search results for "Computer Vision and Pattern Recognition"

Assessing movie similarity using a multilayer network model

2021

International audience; This work investigates the movie similarity issue. A multilayer network model capturing various aspects of the story is built from movie scripts. Based on this representation, movies are compared not from summary or actors but using their storyboard. We rely on the "Portrait divergence" to quantify distances between graph characteristics. We illustrate the effectiveness of this approach in comparing movie series.

Signal-to-noise ratio in reproducing kernel Hilbert spaces

2018

This paper introduces the kernel signal-to-noise ratio (kSNR) for different machine learning and signal processing applications}. The kSNR seeks to maximize the signal variance while minimizing the estimated noise variance explicitly in a reproducing kernel Hilbert space (rkHs). The kSNR gives rise to considering complex signal-to-noise relations beyond additive noise models, and can be seen as a useful signal-to-noise regularizer for feature extraction and dimensionality reduction. We show that the kSNR generalizes kernel PCA (and other spectral dimensionality reduction methods), least squares SVM, and kernel ridge regression to deal with cases where signal and noise cannot be assumed inde…

Edge detection insensitive to changes of illumination in the image

2010

In this paper we present new edge detection algorithms which are motivated by recent developments on edge-adapted reconstruction techniques [F. Arandiga, A. Cohen, R. Donat, N. Dyn, B. Matei, Approximation of piecewise smooth functions and images by edge-adapted (ENO-EA) nonlinear multiresolution techniques, Appl. Comput. Harmon. Anal. 24 (2) (2008) 225-250]. They are based on comparing local quantities rather than on filtering and thresholding. This comparison process is invariant under certain transformations that model light changes in the image, hence we obtain edge detection algorithms which are insensitive to changes in illumination.

How to standardize (if you must)

2017

In many situations we are interested in appraising the value of a certain characteristic for a given individual relative to the context in which this value is observed. In recent years this problem has become prominent in the evaluation of scientific productivity and impact. A popular approach to such relative valuations consists in using percentile ranks. This is a purely ordinal method that may sometimes lead to counterintuitive appraisals, in that it discards all information about the distance between the raw values within a given context. By contrast, this information is partly preserved by using standardization, i.e., by transforming the absolute values in such a way that, within the s…

Fitting flavour symmetries: the case of two-zero neutrino mass textures

2018

We present a numeric method for the analysis of the fermion mass matrices predicted in flavour models. The method does not require any previous algebraic work, it offers a $\chi^{2}$ comparison test and an easy estimate of confidence intervals. It can also be used to study the stability of the results when the predictions are disturbed by small perturbations. We have applied the method to the case of two-zero neutrino mass textures using the latest available fits on neutrino oscillations, derived the available parameter space for each texture and compared them. Textures $A_{1}$ and $A_{2}$ seem favoured because they give a small $\chi^{2}$, allow for large regions in parameter space and giv…

“It Is Not the Robot Who Learns, It Is Me.” Treating Severe Dysgraphia Using Child–Robot Interaction

2021

Writing disorders are frequent and impairing. However, social robots may help to improve children's motivation and to propose enjoyable and tailored activities. Here, we have used the Co-writer scenario in which a child is asked to teach a robot how to write via demonstration on a tablet, combined with a series of games we developed to train specifically pressure, tilt, speed, and letter liaison controls. This setup was proposed to a 10-year-old boy with a complex neurodevelopmental disorder combining phonological disorder, attention deficit/hyperactivity disorder, dyslexia, and developmental coordination disorder with severe dysgraphia. Writing impairments were severe and limited his parti…

RADIOMETRIC CALIBRATION OF A MULTISPECTRAL CAMERA

2006

We describe in detail a method for calibrating a multispectral imaging system based on interference filters. The calibration aims to remove systematic noises introduced by the sensor, and optic and/or filters from multispectral images. After which, we can correct the non-linearity of the sensor response. Systematic noises are measured through a rigorous protocol for acquiring offset, and thermal, and Flat-Field images. The methods for acquiring Flat-Field image, and linearizing sensor response are novel and particularly efficient in the case of a multispectral imaging system. Indeed, in such a system, the reconstruction of a spectrum for each pixel comes from the set of values taken by this…

Corrigendum to “Registration of surfaces minimizing error propagation for a one-shot multi-slit hand-held scanner” [Pattern Recognition 41 (6) 2055–2…

2009

A Planning and Control System for Self-Driving Racing Vehicles

2018

Autonomous robots will soon enter our everyday life as self-driving cars. These vehicles are designed to behave according to certain sets of cooperative rules, such as traffic ones, and to respond to events that might be unpredictable in their occurrence but predictable in their nature, such as a pedestrian suddenly crossing a street, or another car losing control. As civilian autonomous cars will cross the road, racing autonomous cars are under development, which will require superior Artificial Intelligence Drivers to perform in structured but uncertain conditions. We describe some preliminary results obtained during the development of a planning and control system as key elements of an A…

Automated Detection of Optic Disc Location in Retinal Images

2008

This contribution presents an automated method to locate the optic disc in color fundus images. The method uses texture descriptors and a regression based method in order to determine the best circle that fits the optic disc. The best circle is chosen from a set of circles determined with an innovative method, not using the Hough transform as past approaches. An evaluation of the proposed method has been done using a database of 40 images. On this data set, our method achieved 95% success rate for the localization of the optic disc and 70% success rate for the identification of the optic disc contour (as a circle).