Search results for "Computer Vision"
showing 10 items of 2353 documents
A new multimodal RGB and polarimetric image dataset for road scenes analysis
2020
International audience; Road scene analysis is a fundamental task for both autonomous vehicles and ADAS systems. Nowadays, one can find autonomous vehicles that are able to properly detect objects present in the scene in good weather conditions but some improvements are left to be done when the visibility is altered. People claim that using some non conventional sensors (infra-red, Lidar, etc.) along with classical vision enhances road scene analysis but still when conditions are optimal. In this work, we present the improvements achieved using polarimetric imaging in the complex situation of adverse weather conditions. This rich modality is known for its ability to describe an object not o…
Smartphone viewing distance during active or passive tasks and relation to heterophoria
2019
Our aim was to analyze viewing distance for smartphone users (aged 18-45 y.) in terms of passive or active task, relation to heterophoria, type of refractive error and smartphone font size. Participants were asked to read out loud text message (passive task) and afterwards rewrite the same text and send back (active task). For the text message we used sentence consisting of 23 words and 200 characters (with spaces). Participants used their own smartphones (font size monitored). For both passive and active task we measured task time and viewing distance at the end of the task. We found significantly shorter viewing distance for digital active task compared to passive task (29.3 ± 4.7 and 32.…
An automatic filtering algorithm for SURF-based registration of remote sensing images
2017
International audience; The registration of remote sensing images has been often a necessary step for further analyses of images taken at different times, different viewing geometry or with different sensors. For this task there exists many approaches. This paper focuses on the feature-based category of image registration methods. Particularly, we propose an improvement of the SURF algorithm on the point matching step. Indeed, in order to achieve a correct registration, a good matching of feature point is required. However The presence of outliers lead to a fail in the registration. Therefore, in this paper, we introduce an efficient method devoted to the detection and removal of such outli…
3D Reconstruction of Dynamic Vehicles using Sparse 3D-Laser-Scanner and 2D Image Fusion
2016
International audience; Map building becomes one of the most interesting research topic in computer vision field nowadays. To acquire accurate large 3D scene reconstructions, 3D laser scanners are recently developed and widely used. They produce accurate but sparse 3D point clouds of the environments. However, 3D reconstruction of rigidly moving objects along side with the large-scale 3D scene reconstruction is still lack of interest in many researches. To achieve a detailed object-level 3D reconstruction, a single scan of point cloud is insufficient due to their sparsity. For example, traditional Iterative Closest Point (ICP) registration technique or its variances are not accurate and rob…
Image-based MRI Gradient Estimation
2017
In order to reduce geometric distortion phenomena in MR images, every MRI system main magnet undergoes a shimming process. Since this process aims at optimizing magnetic field homogeneity within a so-called uniformity sphere, image quality outside this sphere is neglected. Since the fields vary smoothly in space, MR signal-to-noise ratio is still non-zero just outside the uniformity region, but correction of MR image distortion fails due to lack of magnetic field knowledge outside it. We propose a novel algorithm for measuring all the fields involved in the generation of images. Our proposal is based on exploitation of the distortion which can be observed in images of a known phantom. The p…
Accuracy of a computer vision system for estimating biomechanical measures of body function in axial spondyloarthropathy patients and healthy subjects
2023
Objective Advances in computer vision make it possible to combine low-cost cameras with algorithms, enabling biomechanical measures of body function and rehabilitation programs to be performed anywhere. We evaluated a computer vision system's accuracy and concurrent validity for estimating clinically relevant biomechanical measures. Design Cross-sectional study. Setting Laboratory. Participants Thirty-one healthy participants and 31 patients with axial spondyloarthropathy. Intervention A series of clinical functional tests (including the gold standard Bath Ankylosing Spondylitis Metrology Index tests). Each test was performed twice: the first performance was recorded with a camera, and a co…
Multispectral, Fluorescent and Photoplethysmographic Imaging for Remote Skin Assessment
2017
Optical tissue imaging has several advantages over the routine clinical imaging methods, including non-invasiveness (does not change the structure of tissues), remote operation (avoids infection) and ability to quantify the tissue condition by means of specific image parameters. Dermatologists and other skin experts need compact (preferably pocket-size), self-sustained and easy-to-use imaging devices. The operational principles and designs of ten portable in-vivo skin imaging prototypes developed at the Biophotonics Laboratory of Institute of Atomic Physics and Spectroscopy, University of Latvia during the recent five years are presented in this paper. Four groups of imaging devices are con…
Kernel Spectral Angle Mapper
2016
This communication introduces a very simple generalization of the familiar spectral angle mapper (SAM) distance. SAM is perhaps the most widely used distance in chemometrics, hyperspectral imaging, and remote sensing applications. We show that a nonlinear version of SAM can be readily obtained by measuring the angle between pairs of vectors in a reproducing kernel Hilbert spaces. The kernel SAM generalizes the angle measure to higher-order statistics, it is a valid reproducing kernel, it is universal, and it has consistent geometrical properties that permit deriving a metric easily. We illustrate its performance in a target detection problem using very high resolution imagery. Excellent re…
Contribution à l’apprentissage de représentation de données à base de graphes avec application à la catégorisation d’images
2020
Graph-based Manifold Learning algorithms are regarded as a powerful technique for feature extraction and dimensionality reduction in Pattern Recogniton, Computer Vision and Machine Learning fields. These algorithms utilize sample information contained in the item-item similarity and weighted matrix to reveal the intrinstic geometric structure of manifold. It exhibits the low dimensional structure in the high dimensional data. This motivates me to develop Graph-based Manifold Learning techniques on Pattern Recognition, specially, application to image categorization. The experimental datasets of thesis correspond to several categories of public image datasets such as face datasets, indoor and…
Subsequent Keyframe Generation for Visual Servoing
2021
International audience; In this paper, we study the problem of autonomous and reliable positioning of a camera w.r.t. an object when only this latter is known but not the rest of the scene. We propose to combine the advantages and efficiency of a visual servoing scheme and the generalization ability of a generative adversarial network. The paper describes how to efficiently create a synthetic dataset in order to train a network that predicts an intermediate visual keyframe between two images. Subsequent predictions are used as visual features to autonomously converge towards the desired pose even for large displacements. We show that the proposed method can be used without any prior knowled…