Search results for "Computer Vision and Pattern Recognition"
showing 10 items of 997 documents
Irregular motion recovery in fluorescein angiograms
1997
Abstract Fluorescein angiography is a common procedure in ophthalmic practice, mainly to evaluate vascular retinopathies and choroidopathies from sequences of ocular fundus images. In order to compare the images, a reliable overlying is essential. This paper proposes some methods for the recovery of irregular motion in fluorescein angiograms (FA). The overlying is done by a three step procedure: detection of relevant points, matching points from different images and estimation of the assumed linear geometric transformation. A stochastic model (closely related to the general linear model) allows to fuse the second and third steps. Two different estimators of the geometric transformation are …
Order statistics-based parametric classification for multi-dimensional distributions
2013
Traditionally, in the field of Pattern Recognition (PR), the moments of the class-conditional densities of the respective classes have been used to perform classification. However, the use of phenomena that utilized the properties of the Order Statistics (OS) were not reported. Recently, in [10,8], we proposed a new paradigm named CMOS, Classification by the Moments of Order Statistics, which specifically used these quantifiers. It is fascinating that CMOS is essentially ''anti''-Bayesian in its nature because the classification is performed in a counter-intuitive manner, i.e., by comparing the testing sample to a few samples distant from the mean, as opposed to the Bayesian approach in whi…
Estimation of Purkinje trees from electro-anatomical mapping of the left ventricle using minimal cost geodesics
2015
The electrical activation of the heart is a complex physiological process that is essential for the understanding of several cardiac dysfunctions, such as ventricular tachycardia (VT). Nowadays, patient-specific activation times on ventricular chambers can be estimated from electro-anatomical maps, providing crucial information to clinicians for guiding cardiac radio-frequency ablation treatment. However, some relevant electrical pathways such as those of the Purkinje system are very difficult to interpret from these maps due to sparsity of data and the limited spatial resolution of the system. We present here a novel method to estimate these fast electrical pathways from the local activati…
Gesture recognition using low-cost devices: Techniques, applications, perspectives
2016
Negli ultimi anni abbiamo assistito ad una grande diffusione dei cosiddetti “Kinect-like devices”, ovvero dispositivi basati su un insieme di sensori a basso costo, che consentono di ottenere un’immagine di profondità della scena ripresa. L’alta accessibilità di questi dispositivi, principalmente in termini di costi, ne ha facilitato la diffusione nell’ambito del riconoscimento dei gesti in numerose applicazioni, sia commerciali che di ricerca. In questo articolo saranno inizialmente illustrati i principi generali su cui si fondano le principali tecniche utilizzate per riconoscere i gesti, sfruttando i dati ottenibili dai dispositivi “Kinect-like”. Successivamente, saranno presentati alcuni…
Conjugate Gradient Method for Brain Magnetic Resonance Images Segmentation
2018
Part 8: Pattern Recognition and Image Processing; International audience; Image segmentation is the process of partitioning the image into regions of interest in order to provide a meaningful representation of information. Nowadays, segmentation has become a necessity in many practical medical imaging methods as locating tumors and diseases. Hidden Markov Random Field model is one of several techniques used in image segmentation. It provides an elegant way to model the segmentation process. This modeling leads to the minimization of an objective function. Conjugate Gradient algorithm (CG) is one of the best known optimization techniques. This paper proposes the use of the nonlinear Conjugat…
Outdoor Scenes Pixel-wise Semantic Segmentation using Polarimetry and Fully Convolutional Network
2019
International audience; In this paper, we propose a novel method for pixel-wise scene segmentation application using polarimetry. To address the difficulty of detecting highly reflective areas such as water and windows, we use the angle and degree of polarization of these areas, obtained by processing images from a polarimetric camera. A deep learning framework, based on encoder-decoder architecture, is used for the segmentation of regions of interest. Different methods of augmentation have been developed to obtain a sufficient amount of data, while preserving the physical properties of the polarimetric images. Moreover, we introduce a new dataset comprising both RGB and polarimetric images…
A Specialized Architecture for Color Image Edge Detection Based on Clifford Algebra
2013
Edge detection of color images is usually performed by applying the traditional techniques for gray-scale images to the three color channels separately. However, human visual perception does not differentiate colors and processes the image as a whole. Recently, new methods have been proposed that treat RGB color triples as vectors and color images as vector fields. In these approaches, edge detection is obtained extending the classical pattern matching and convolution techniques to vector fields. This paper proposes a hardware implementation of an edge detection method for color images that exploits the definition of geometric product of vectors given in the Clifford algebra framework to ex…
Fast, Reliable Head Tracking Under Varying Illumination
2003
An improved technique for 3D head tracking under varying illumination conditions is proposed. The head is modeled as a texture mapped cylinder. Tracking is formulated as an image registration problem in the cylinder's texture map image. To solve the registration problem in the presence of lighting variation and head motion, the residual error of registration is modeled as a linear combination of texture warping templates and orthogonal illumination templates. Fast and stable on-line tracking is then achieved via regularized weighted least squares minimization of the registration error. The regularization term tends to limit potential ambiguities that arise in the warping and illumination te…
Comparison of region of interest segmentation methods for video-based heart rate measurements
2018
International audience; Conventional contact photoplethysmography (PPG) sensors are not suitable in situations of skin damage or when unconstrained movement is required. As a consequence, remote photoplethysmography (rPPG) has recently emerged because it provides remote physiological measurements without expensive hardware and improves comfort for long-term monitoring. RPPG estimation methods use the spatially averaged RGB values of pixels in a Region Of Interest (ROI) to generate a temporal RGB signal. The selection of ROI is a critical first step to obtain reliable pulse signals and must contain as many skin pixels as possible with a low percentage of non-skin pixels. In this paper, we ex…
Remote Photoplethysmography measurement using constrained ICA
2017
Remote Photoplethysmography (rPPG) is a technique that consists in estimating physiological parameters such as heart rate from live or recorded video sequences taken by conventional camera or even webcams. This technique is increasingly used in many application fields thanks to its simplicity and affordability. The basic idea is that the arterial blood flow shows regularity due to the heartbeat. This regularity is manifested by very small periodic variations in the color of the skin, which can be isolated and quantified by signal and image processing methods. In this context, Independent Component Analysis (ICA) is largely used to separate the signal due to arterial flow from signals from o…