Search results for "METHODOLOGIE"
showing 10 items of 2141 documents
Learning spatial filters for multispectral image segmentation.
2010
International audience; We present a novel filtering method for multispectral satel- lite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments car- ried out on multiclass one-against-all classification and tar- get detection show the capabilities of the learned spatial fil- ters.
Support Vector Machine and Kernel Classification Algorithms
2018
This chapter introduces the basics of support vector machine (SVM) and other kernel classifiers for pattern recognition and detection. It also introduces the main elements and concept underlying the successful binary SVM. The chapter starts by introducing the main elements and concept underlying the successful binary SVM. Next, it introduces more advanced topics in SVM for classification, including large margin filtering (LMF), SSL, active learning, and large‐scale classification using SVMs. The LMF method performs both signal filtering and classification simultaneously by learning the most appropriate filters. SSL with SVMs exploits the information contained in both labeled and unlabeled e…
Calibrating a Motion Model Based on Reinforcement Learning for Pedestrian Simulation
2012
In this paper, the calibration of a framework based in Multi-agent Reinforcement Learning (RL) for generating motion simulations of pedestrian groups is presented. The framework sets a group of autonomous embodied agents that learn to control individually its instant velocity vector in scenarios with collisions and friction forces. The result of the process is a different learned motion controller for each agent. The calibration of both, the physical properties involved in the motion of our embodied agents and the corresponding dynamics, is an important issue for a realistic simulation. The physics engine used has been calibrated with values taken from real pedestrian dynamics. Two experime…
Kinematic calibration method for a 5-DOF Gantry-Tau parallel kinematic machine
2013
In this paper a new step-wise approach to kinematic calibration of a 5-DOF Gantry-Tau parallel kinematic machine (PKM) is presented. The approach can be adapted to the modular design of the PKM and the calibration could easily perform part of the assembly instructions for the machine. By using measurements from a laser tracker and least-squares estimates of polynomial functions, a typical accuracy of about 20 micrometer was achieved for the base actuators. The remaining set of 30 general parameters for the hexapod link structure and spherical joint connections were successfully estimated using the Complex search-based evolutionary algorithm.
A GPU-Based DVC to H.264/AVC Transcoder
2010
Mobile to mobile video conferencing is one of the services that the newest mobile network operators can offer to users With the apparition of the distributed video coding paradigm which moves the majority of complexity from the encoder to the decoder, this offering can be achieved by introducing a transcoder This device has to convert from the distributed video coding paradigm to traditional video coding such as H.264/AVC which is formed by simpler decoders and more complex encoders, and allows to the users to execute only the low complex algorithms In order to deal with this high complex video transcoder, this paper introduces a graphics processing unit based transcoder as base station The…
Restoration of Videos Degraded by Local Isoplanatism Effects in the Near-Infrared Domain
2008
When observing a scene horizontally at a long distance in the near-infrared domain, degradations due to atmospheric turbulence often occur. In our previous work, we presented two hybrid methods to restore videos degraded by such local perturbations. These restoration algorithms take advantages of a space-time Wiener filter and a space-time regularization by the Laplacian operator. Wiener and Laplacian regularization results are mixed differently depending on the distance between the current pixel and the nearest edge point. It was shown that a gradation between Wiener and Laplacian areas improves results quality, so that only the algorithm using a gradation will be used in this article. In …
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…
Combining Supervised and Unsupervised Learning to Discover Emotional Classes
2017
Most previous work in emotion recognition has fixed the available classes in advance, and attempted to classify samples into one of these classes using a supervised learning approach. In this paper, we present preliminary work on combining supervised and unsupervised learning to discover potential latent classes which were not initially considered. To illustrate the potential of this hybrid approach, we have used a Self-Organizing Map (SOM) to organize a large number of Electroencephalogram (EEG) signals from subjects watching videos, according to their internal structure. Results suggest that a more useful labelling scheme could be produced by analysing the resulting topology in relation t…