Search results for "VISION"
showing 10 items of 5066 documents
Complex networks : application for texture characterization and classification
2008
This article describes a new method and approch of texture characterization. Using complex network representation of an image, classical and derived (hierarchical) measurements, we presente how to have good performance in texture classification. Image is represented by a complex networks : one pixel as a node. Node degree and clustering coefficient, using with traditionnal and extended hierarchical measurements, are used to characterize ”organisation” of textures.
Extended constrained deformations: a new sculpturing tool
1999
Modelling tools tend to virtual sculpturing, in which a basic object is deformed by user supplied actions. The model we present aims to be generic: whatever the geometric description of the object, we can deform it to satisfy location constraints. Our model deforms the whole space, the image of a point is a blend of deformation functions with a projection matrix which allows the satisfaction of the constraints. The user can define the extent of the deformation (i.e. the part of the object to be deformed), the shape of the deformation function to create profiles and the displacement of the constraint points to be satisfied.
Chess recognition using 3D patterned illumination camera
2021
Computer Vision has been applied to augment traditional board games such as Chess for a number of reasons. While augmented reality enhances the gaming experience, the required additional hardware (e.g. head gear) is still not widely accepted in everyday leisure activities, and therefore, camera based methods have been developed to interface the computer with the real-life chess board. However, traditional 2D camera approaches suffer from ill-defined environmental conditions (lighting, viewing angle) and are therefore severely limited in their application. To answer this issue, we have incorporated a consumer-grade depth camera based on patterned illumination. We could show that in combinati…
Deep multimodal fusion for semantic image segmentation: A survey
2021
International audience; Recent advances in deep learning have shown excellent performance in various scene understanding tasks. However, in some complex environments or under challenging conditions, it is necessary to employ multiple modalities that provide complementary information on the same scene. A variety of studies have demonstrated that deep multimodal fusion for semantic image segmentation achieves significant performance improvement. These fusion approaches take the benefits of multiple information sources and generate an optimal joint prediction automatically. This paper describes the essential background concepts of deep multimodal fusion and the relevant applications in compute…
Stereopsis assessment at multiple distances with an iPad application
2017
[EN] We present a new application for iPad for screening stereopsis at multiple distances that allows testing up to ten levels of stereoacuity at each distance. Our approach is based on a random dot stereogram viewable with anaglyph spectacles. Sixty-five subjects with no ocular diseases, wearing their habitual correction were measured at 3 m and 0.5 m. Results were compared with a standard stereoscopic test (TNO). We found not statistically significant differences between both tests, but our method achieved higher reproducibility. Applications in visual screening programs and to design and use of 3D displays, are suggested. (C) 2017 Elsevier B.V. All rights reserved.
A Framework for Activity Monitoring and Fall Detection Based on the Characteristics of Indoor Channels
2018
Author´s accepted manuscript © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper concerns the Doppler power spectrum of three-dimensional non-stationary indoor fixed-to- fixed channels with moving people. In this paper, we model each moving person as a moving scatterer with time-variant (TV) speed, TV vertical angles of motion, and TV horizontal angles o…
Machine Learning Techniques for Intrusion Detection: A Comparative Analysis
2016
International audience; With the growth of internet world has transformed into a global market with all monetary and business exercises being carried online. Being the most imperative resource of the developing scene, it is the vulnerable object and hence needs to be secured from the users with dangerous personality set. Since the Internet does not have focal surveillance component, assailants once in a while, utilizing varied and advancing hacking topologies discover a path to bypass framework " s security and one such collection of assaults is Intrusion. An intrusion is a movement of breaking into the framework by compromising the security arrangements of the framework set up. The techniq…
Automated prostate gland segmentation based on an unsupervised fuzzy C-means clustering technique using multispectral T1w and T2w MR imaging
2017
Prostate imaging analysis is difficult in diagnosis, therapy, and staging of prostate cancer. In clinical practice, Magnetic Resonance Imaging (MRI) is increasingly used thanks to its morphologic and functional capabilities. However, manual detection and delineation of prostate gland on multispectral MRI data is currently a time-expensive and operator-dependent procedure. Efficient computer-assisted segmentation approaches are not yet able to address these issues, but rather have the potential to do so. In this paper, a novel automatic prostate MR image segmentation method based on the Fuzzy C-Means (FCM) clustering algorithm, which enables multispectral T1-weighted (T1w) and T2-weighted (T…
Representation of NURBS surfaces by Controlled Iterated Functions System automata
2019
Iterated Function Systems (IFS) are a standard tool to generate fractal shapes. In a more general way, they can represent most of standard surfaces like Bézier or B-Spline surfaces known as self-similar surfaces. Controlled Iterated Function Systems (CIFS) are an extension of IFS based on automata. CIFS are basically multi-states IFS, they can handle all IFS shapes but can also manage multi self-similar shapes. For example CIFS can describe subdivision surfaces around extraordinary vertices whereas IFS cannot. Having a common CIFS formalism facilitates the development of generic methods to manage interactions (junctions, differences...) between objects of different natures.This work focuses…
Efficient linear fusion of partial estimators
2018
Abstract Many signal processing applications require performing statistical inference on large datasets, where computational and/or memory restrictions become an issue. In this big data setting, computing an exact global centralized estimator is often either unfeasible or impractical. Hence, several authors have considered distributed inference approaches, where the data are divided among multiple workers (cores, machines or a combination of both). The computations are then performed in parallel and the resulting partial estimators are finally combined to approximate the intractable global estimator. In this paper, we focus on the scenario where no communication exists among the workers, de…