Search results for "image processing"
showing 10 items of 3285 documents
Convolutional Matrix Factorization for Recommendation Explanation
2018
In this paper, we introduce a novel recommendation model, which harnesses a convolutional neural network to mine meaningful information from customer reviews, and integrates it with matrix factorization algorithm seamlessly. It is a valid method to improve the transparency of CF algorithms.
Automatic recognition of tree species from 3D point clouds of forest plots
2014
The objective of the thesis is the automatic recognition of tree species from Terrestrial LiDAR data. This information is essential for forest inventory. As an answer, we propose different recognition methods based on the 3D geometric texture of the bark.These methods use the following processing steps: a preprocessing step, a segmentation step, a feature extraction step and a final classification step. They are based on the 3D data or on depth images built from 3D point clouds of tree trunks using a reference surface.We have investigated and tested several segmentation approaches on depth images representing the geometric texture of the bark. These approaches have the disadvantages of over…
Image-based detection and classification of allergenic pollen
2015
The correct classification of airborne pollen is relevant for medical treatment of allergies, and the regular manual process is costly and time consuming. An automatic processing would increase considerably the potential of pollen counting. Modern computer vision techniques enable the detection of discriminant pollen characteristics. In this thesis, a set of relevant image-based features for the recognition of top allergenic pollen taxa is proposed and analyzed. The foundation of our proposal is the evaluation of groups of features that can properly describe pollen in terms of shape, texture, size and apertures. The features are extracted on typical brightfield microscope images that enable…
Selection of optimal narrowband multispectral images for face recognition
2015
Face recognition systems based on ’conventional’ images have reached a significant level of maturity with some practical successes. However, their performance may degrade under poor and/or changing illumination. Multispectral imagery represents a viable alternative to conventional imaging in the search for a robust and practical identification system. Multi- spectral imaging (MI) can be defined as a ’collection of several monochrome images of the same scene, each of them taken with additional receptors sensitive to other frequencies of the visible light or to frequencies beyond the visible light like the infrared region of electro- magnetic continuum. Each image is referred to as a band or …
Graph recursive least squares filter for topology inference in causal data processes
2017
In this paper, we introduce the concept of recursive least squares graph filters for online topology inference in data networks that are modelled as Causal Graph Processes (CGP). A Causal Graph Process (CGP) is an auto regressive process in the time series associated to different variables, and whose coefficients are the so-called graph filters, which are matrix polynomials with different orders of the graph adjacency matrix. Given the time series of data at different variables, the goal is to estimate these graph filters, hence the associated underlying adjacency matrix. Previously proposed algorithms have focused on a batch approach, assuming implicitly stationarity of the CGP. We propose…
Accelerating H.264 inter prediction in a GPU by using CUDA
2010
H.264/AVC defines a very efficient algorithm for the inter prediction but it takes too much time. With the emergence of General Purpose Graphics Processing Units (GPGPU), a new door has been opened to support this video algorithm into these small processing units. In this paper, a forward step is developed towards an implementation of the H.264/AVC inter prediction algorithm into a GPU using Compute Unified Device Architecture (CUDA). The results show a negligible rate distortion drop with a time reduction on average up to 93.6%.
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…
Regularization operators for natural images based on nonlinear perception models.
2006
Image restoration requires some a priori knowledge of the solution. Some of the conventional regularization techniques are based on the estimation of the power spectrum density. Simple statistical models for spectral estimation just take into account second-order relations between the pixels of the image. However, natural images exhibit additional features, such as particular relationships between local Fourier or wavelet transform coefficients. Biological visual systems have evolved to capture these relations. We propose the use of this biological behavior to build regularization operators as an alternative to simple statistical models. The results suggest that if the penalty operator take…
On Regulated Solutions of Impulsive Differential Equations with Variable Times
2020
In this paper we investigate the unified theory for solutions of differential equations without impulses and with impulses, even at variable times, allowing the presence of beating phenomena, in the space of regulated functions. One of the aims of the paper is to give sufficient conditions to ensure that a regulated solution of an impulsive problem is globally defined.