Search results for "image processing"
showing 10 items of 3285 documents
A reconfigurable architecture for autonomous visual-navigation
2003
This paper describes the design of a reconfigurable architecture for implementing image processing algorithms. This architecture is a pipeline of small identical processing elements that contain a programmable logic device (FPGA) and double port memories. This processing system has been adapted to accelerate the computation of differential algorithms. The log-polar vision selectively reduces the amount of data to be processed and simplifies several vision algorithms, making possible their implementation using few hard-ware resources. The reconfigurable architecture design has been devoted to implementation, and has been employed in an autonomous platform, which has power consumption, size a…
Directive local color transfer based on dynamic look-up table
2019
Abstract Color transfer in image processing usually suffers from misleading color mapping and loss of details. This paper presents a novel directive local color transfer method based on dynamic look-up table (D-DLT) to solve these problems in two steps. First, a directive mapping between the source and the reference image is established based on the salient detection and the color clusters to obtain directive color transfer intention. Then, dynamic look-up tables are created according to the color clusters to preserve the details, which can suppress pseudo contours and avoid detail loss. Subjective and objective assessments are presented to verify the feasibility and the availability of the…
Benchmarking non-photorealistic rendering of portraits
2017
We present a set of images for helping NPR practitioners evaluate their image-based portrait stylisation algorithms. Using a standard set both facilitates comparisons with other methods and helps ensure that presented results are representative. We give two levels of difficulty, each consisting of 20 images selected systematically so as to provide good coverage of several possible portrait characteristics. We applied three existing portrait-specific stylisation algorithms, two general-purpose stylisation algorithms, and one general learning based stylisation algorithm to the first level of the benchmark, corresponding to the type of constrained images that have often been used in portrait-s…
Development of a fast panoramic face mosaicking and recognition system
2005
We present some development results on a system that per- forms mosaicking of panoramic faces. Our objective is to study the fea- sibility of panoramic face construction in real time. To do so, we built a simple acquisition system composed of five standard cameras, which together can take simultaneously five views of a face at different angles. Then, we chose an easily hardware-achievable algorithm, consisting of successive linear transformations, in order to compose a panoramic face from these five views. The method has been tested on a large number of faces. In order to validate our system, we also conducted a preliminary study on panoramic face recognition, based on the principal-compone…
Camera-LiDAR Data Fusion for Autonomous Mooring Operation
2020
Author's accepted manuscript. © 2020 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. The use of camera and LiDAR sensors to sense the environment has gained increasing popularity in robotics. Individual sensors, such as cameras and LiDARs, fail to meet the growing challenges in complex autonomous systems. One such scenario is autonomous mooring, where the ship has to …
Towards a SDN-based architecture for analyzing network traffic in cloud computing infrastructures
2015
Currently, network traffic monitoring tools do not fit well in the monitoring of cloud computing infrastructures. These tools are not integrated with the control plane of the cloud computing stack. This lack of integration causes a deficiency in the handling of the re-usage of IP addresses along virtual machines, a lack of adaption and reaction on highly frequent topology changes, and a lack of accuracy in the metrics gathered for the networking traffic flowing along the cloud infrastructure. The main contribution of this paper is to provide a novel SDN-based architecture to carry out the monitoring of network traffic in cloud infrastructures. The architecture in based on the integration be…
Learning Flow-Based Feature Warping for Face Frontalization with Illumination Inconsistent Supervision
2020
Despite recent advances in deep learning-based face frontalization methods, photo-realistic and illumination preserving frontal face synthesis is still challenging due to large pose and illumination discrepancy during training. We propose a novel Flow-based Feature Warping Model (FFWM) which can learn to synthesize photo-realistic and illumination preserving frontal images with illumination inconsistent supervision. Specifically, an Illumination Preserving Module (IPM) is proposed to learn illumination preserving image synthesis from illumination inconsistent image pairs. IPM includes two pathways which collaborate to ensure the synthesized frontal images are illumination preserving and wit…
Multiscale Attention-Based Prototypical Network For Few-Shot Semantic Segmentation
2021
International audience; Deep learning-based image understanding techniques require a large number of labeled images for training. Few-shot semantic segmentation, on the contrary, aims at generalizing the segmentation ability of the model to new categories given only a few labeled samples. To tackle this problem, we propose a novel prototypical network (MAPnet) with multiscale feature attention. To fully exploit the representative features of target classes, we firstly extract rich contextual information of labeled support images via a multiscale feature enhancement module. The learned prototypes from support features provide further semantic guidance on the query image. Then we adaptively i…
Proposition of Convolutional Neural Network Based System for Skin Cancer Detection
2019
Skin cancer automated diagnosis tools play a vital role in timely screening, helping dermatologists focus on melanoma cases. Best arts on automated melanoma screening use deep learning-based approaches, especially deep convolutional neural networks (CNN) to improve performances. Because of the large number of parameters that could be involved during training in CNN many training samples are needed to avoid overfitting problem. Gabor filtering can efficiently extract spatial information including edges and textures, which may reduce the features extraction burden to CNN. In this paper, we proposed a Gabor Convolutional Network (GCN) model to improve the performance of automated diagnosis of …
Combination Of Handcrafted And Deep Learning-Based Features For 3d Mesh Quality Assessment
2020
We propose in this paper a novel objective method to evaluate the perceived visual quality of 3D meshes. The proposed method in no-reference, it relies only on the distorted mesh for the quality estimation. It is based on a pre-trained convolutional neural network (i.e VGG to extract features from the distorted mesh) and handcrafted features extracted directly from the 3D mesh (i.e curvature and dihedral angle). A General Regression Neural Network (GRNN) is used to learn the statistical parameters of the feature vectors and estimate the quality score. Experimental results from for subjective databases (LIRIS masking, LIRIS/EPFL generalpurpose, UWB compression and LEETA simplification) and c…