Search results for " image processing."
showing 10 items of 2265 documents
Adaptive Importance Sampling: The past, the present, and the future
2017
A fundamental problem in signal processing is the estimation of unknown parameters or functions from noisy observations. Important examples include localization of objects in wireless sensor networks [1] and the Internet of Things [2]; multiple source reconstruction from electroencephalograms [3]; estimation of power spectral density for speech enhancement [4]; or inference in genomic signal processing [5]. Within the Bayesian signal processing framework, these problems are addressed by constructing posterior probability distributions of the unknowns. The posteriors combine optimally all of the information about the unknowns in the observations with the information that is present in their …
Knowledge acquisition through introspection in Human-Robot Cooperation
2018
Abstract When cooperating with a team including humans, robots have to understand and update semantic information concerning the state of the environment. The run-time evaluation and acquisition of new concepts fall in the critical mass learning. It is a cognitive skill that enables the robot to show environmental awareness to complete its tasks successfully. A kind of self-consciousness emerges: the robot activates the introspective mental processes inferring if it owns a domain concept or not, and correctly blends the conceptual meaning of new entities. Many works attempt to simulate human brain functions leading to neural network implementation of consciousness; regrettably, some of thes…
A self-adaptable distributed CBR version of the EquiVox system
2016
Three dimensional (3D) voxel phantoms are numerical representations of human bodies, used by physicians in very different contexts. In the controlled context of hospitals, where from 2 to 10 subjects may arrive per day, phantoms are used to verify computations before therapeutic exposure to radiation of cancerous tumors. In addition, 3D phantoms are used to diagnose the gravity of accidental exposure to radiation. In such cases, there may be from 10 to more than 1000 subjects to be diagnosed simultaneously. In all of these cases, computation accuracy depends on a single such representation. In this paper, we present EquiVox which is a tool composed of several distributed functions and enab…
Computation of Psycho-Acoustic Annoyance Using Deep Neural Networks
2019
Psycho-acoustic parameters have been extensively used to evaluate the discomfort or pleasure produced by the sounds in our environment. In this context, wireless acoustic sensor networks (WASNs) can be an interesting solution for monitoring subjective annoyance in certain soundscapes, since they can be used to register the evolution of such parameters in time and space. Unfortunately, the calculation of the psycho-acoustic parameters involved in common annoyance models implies a significant computational cost, and makes difficult the acquisition and transmission of these parameters at the nodes. As a result, monitoring psycho-acoustic annoyance becomes an expensive and inefficient task. Thi…
Logical Key Hierarchy for Group Management in Distributed Online Social Networks
2016
Distributed Online Social Networks (DOSNs) have recently been proposed to shift the control over user data from a unique entity to the users of the DOSN themselves. In this paper, we focus our attention on the problem of privacy preserving content sharing to a large group of users of the DOSNs. Several solutions, based on cryptographic techniques, have been recently proposed. The main challenge here is the definition of a scalable and decentralized approach that: i) minimizes the re-encryption of the contents published in a group when the composition of the group changes and ii) enables a fast distribution of the cryptographic keys to all the members (n) of a group, each time a new user is …
Unmanned Aerial Vehicle-Based Non Destructive Diagnostics
2018
The paper proposes a cloud platform for analyzing the radiometric infrared videos uploaded by drones which patrol large photovoltaic plants. Thanks to artificial vision algorithms, it does not require any human support to select and associate the framed PV modules to the corresponding ones in the topology of the photovoltaic plant. The algorithm implements an innovative diagnostic protocol, which evaluates the thermal state of the photovoltaic module, whichever the environmental conditions are. The data automatically computed and collected in a multimedia database provide the O&M technicians with significant information to monitor the ageing of each module of the photovoltaic plant. The pro…
Automatic Calibration of an Industrial RGB-D Camera Network Using Retroreflective Fiducial Markers
2019
This paper describes a non-invasive, automatic, and robust method for calibrating a scalable RGB-D sensor network based on retroreflective ArUco markers and the iterative closest point (ICP) scheme. We demonstrate the system by calibrating a sensor network comprised of six sensor nodes positioned in a relatively large industrial robot cell with an approximate size of 10 m × 10 m × 4 m . Here, the automatic calibration achieved an average Euclidean error of 3 c m at distances up to 9.45 m . To achieve robustness, we apply several innovative techniques: Firstly, we mitigate the ambiguity problem that occurs when detecting a marker at long range or low resolution by comparing the…
Ownership protection of plenoptic images by robust and reversible watermarking
2018
Abstract Plenoptic images are highly demanded for 3D representation of broad scenes. Contrary to the images captured by conventional cameras, plenoptic images carry a considerable amount of angular information, which is very appealing for 3D reconstruction and display of the scene. Plenoptic images are gaining increasing importance in areas like medical imaging, manufacturing control, metrology, or even entertainment business. Thus, the adaptation and refinement of watermarking techniques to plenoptic images is a matter of raising interest. In this paper a new method for plenoptic image watermarking is proposed. A secret key is used to specify the location of logo insertion. Employing discr…
Extrinsic calibration of heterogeneous cameras by line images
2014
International audience; The extrinsic calibration refers to determining the relative pose of cameras. Most of the approaches for cameras with non-overlapping fields of view (FOV) are based on mirror reflection, object tracking or rigidity constraint of stereo systems whereas cameras with overlapping FOV can be calibrated using structure from motion solutions. We propose an extrinsic calibration method within structure from motion framework for cameras with overlapping FOV and its extension to cameras with partially non-overlapping FOV. Recently, omnidirectional vision has become a popular topic in computer vision as an omnidirectional camera can cover large FOV in one image. Combining the g…
Multimodal Images Classification using Dense SURF, Spectral Information and Support Vector Machine
2019
International audience; The multimodal image classification is a challenging area of image processing which can be used to examine the wall painting in the cultural heritage domain. In such classification, a common space of representation is important. In this paper, we present a new method for multimodal representation learning, by using a pixel-wise feature descriptor named dense Speed Up Robust Features (SURF) combined with the spectral information carried by the pixel. For classification of extracted features we have used support vector machine (SVM). Our database was extracted from acquisition on cultural heritage wall paintings that contain four modalities UV, Visible, IRR and fluores…