Electronic Letters on Computer Vision and Image Analysis最新文献

{"title":"Monitoring Infants by Automatic Video Processing","authors":"L. Cattani","doi":"10.5565/REV/ELCVIA.983","DOIUrl":"https://doi.org/10.5565/REV/ELCVIA.983","url":null,"abstract":"This work has, as its objective, the development of non-invasive and low-cost systems for monitoring and automatic diagnosing specific neonatal diseases by means of the analysis of suitable video signals. We focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts. Seizures and respiratory diseases are specifically considered, but the approach is general. Seizures are defined as sudden neurological and behavioural alterations. They are age-dependent phenomena and the most common sign of central nervous system dysfunction. Studies indicate an incidence rate of neonatal seizures of 2‰ for live births, 11‰ for preterm neonates, and 13‰ for infants weighing less than 2500 g at birth. Seizures in newborns have to be promptly and accurately recognized in order to establish timely treatments that could avoid an increase of the underlying brain damage. Respiratory diseases related to the occurrence of apnoea episodes may be caused by cerebrovascular events. Among the wide range of causes of apnoea, besides seizures, a relevant one is Congenital Central Hypoventilation Syndrome (CCHS). With a reported prevalence of 1 in 200,000 live births, CCHS, formerly known as Ondine’s curse, is a rare life-threatening disorder characterized by a failure of the automatic control of breathing, caused by mutations in a gene classified as PHOX2B. The reported mortality rates range from 8% to 38% of newborn with genetically confirmed CCHS. Nowadays, CCHS is considered a disorder of autonomic regulation, with related risk of sudden infant death syndrome (SIDS). Currently, the standard method of diagnosis, for both diseases, is based on polysomnography, a set of sensors such as ElectroEncephaloGram (EEG) sensors, ElectroMyoGraphy (EMG) sensors, ElectroCardio-Graphy (ECG) sensors, elastic belt sensors, pulse-oximeter and nasal flow-meters. This monitoring system is very expensive, time-consuming, moderately invasive and requires particularly skilled medical personnel, not always available in a Neonatal Intensive Care Unit (NICU). Therefore, automatic, real-time and noninvasive monitoring equipments able to reliably recognize these diseases would be of significant value in the NICU. A very appealing monitoring tool to automatically detect neonatal seizures or breathing disorders may be based on acquiring, through a network of sensors, e.g., a set of video cameras, the movements of the newborn’s body (e.g., limbs, chest) and properly processing the relevant signals. An automatic multi-sensor system could be used to permanently monitor every patient in the NICU or specific patients at home. Furthermore, a wire-free technique may be more user-friendly and highly desirable when used with infants, in particular with newborns. We have focused on a reliable method to estimate the periodicity in pathological movements based on the use of the Maximum Likelihood (ML) criterion. In particular, av","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"15 1","pages":"10-12"},"PeriodicalIF":0.0,"publicationDate":"2016-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82906455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New contributions on line-projections in omnidirectional vision","authors":"J. Bermudez-Cameo","doi":"10.5565/REV/ELCVIA.948","DOIUrl":"https://doi.org/10.5565/REV/ELCVIA.948","url":null,"abstract":"Computer vision has an increasing interest in most fields of emerging technologies. A challenging topic in this field is to study how to enlarge the field of view of the camera systems to obtain more information of the environment in a single view. In particular, omnidirectional vision can be useful in many applications such as estimating location in robotics, autonomous driving and unmanned aerial vehicles. The wide field of view of omnidirectional cameras allows taking advantage of describing 3D scenarios using line features. On the one hand, line features represent natural landmarks in man-made environments, they are easy to understand, coincident with edges of constructive elements and often still present when having texture-less scenarios. On the other hand, long segments are especially useful for drift compensation because they are usually completely visible on the omnidirectional projection. However, in omnidirectional cameras line projections are distorted by the projection mapping becoming complex curves. This thesis is focused on the geometry of line projections (line-images) in omnidirectional systems. Main addressed topic of this work is line-image extraction on different kinds of central and non-central omnidirectional images. However, due to the nature of projection in omnidirectional cameras, other addressed topics are camera calibration and, in the case on non-central cameras, 3D reconstruction from single images.","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"17 1","pages":"24-26"},"PeriodicalIF":0.0,"publicationDate":"2016-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75357557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image Processing Algorithms for Driver Assistance using Wide Angle Cameras","authors":"Sebastian Houben","doi":"10.5565/REV/ELCVIA.943","DOIUrl":"https://doi.org/10.5565/REV/ELCVIA.943","url":null,"abstract":"Modern vehicles are deployed with a large number of sensors in order to provide a rich spectrum of driver assistance functionality. These systems enhance security and comfort of passengers and other traffic participants alike, but they also pave the road to fully autonomous traffic. In order to provide this functionality robustly and reliably, one currently makes use of numerous specialized sensors: laser, radar, ultrasound, and infrared sensors, as well as different kinds of video cameras. The diversity of sensors comes with high cost and enables complex assistance functions momentarily only for upper-class vehicles. The current research, thus, focuses on the development of better algorithms that make similar systems possible on inexpensive sensors. This thesis examines the aptitude of a new camera system, which has recently grown popular in vehicles of most of the large automobile manufacturers, for all major video-based driver assistance functionality. This so-called  Topview system consists of four wide angle cameras with a view angle of up to 200 degrees , usually mounted at the front bumper, the two side mirrors and the trunk lid. By these means, one is able to provide a view surrounding the entire vehicle. However, the single camera images are distorted which substantiates the need for adapted image processing algorithms.","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"28 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2016-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80665614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contributions to Real-time Metric Localisation with Wearable Vision Systems","authors":"D. Gutiérrez","doi":"10.5565/REV/ELCVIA.951","DOIUrl":"https://doi.org/10.5565/REV/ELCVIA.951","url":null,"abstract":"Under the rapid development of electronics and computer science in the last years, cameras have become omnipresent nowadays, to such extent that almost everybody is able to carry one at all times embedded into their cellular phone. What makes cameras specially appealing for us is their ability to quickly capture a lot of information of the environment encoded in one image or video, allowing us to immortalize special moments inour life or share reliable visual information of the environment with other persons. However, while the task ofextracting the information from an image may by trivial for us, in the case of computers complex algorithmswith a high computational burden are required to transform a raw image into useful information. In this sense, the same rapid development in computer science that allowed the widespread of cameras has enabled also the possibility of real-time application of previously practically infeasible algorithms. Among the current fields of research in the computer vision community, this thesis is specially concerned in metric localisation and mapping algorithms. These algorithms are a key component in many practical applications such as robot navigation, augmented reality or reconstructing 3D models of the environment. The goal of this thesis  is to delve into visual localisation and mapping from vision, paying special attention to conventional and unconventional cameras which can be easily worn or handled by a human. In this thesis I contribute in the following aspects of the visual odometry and SLAM (Simultaneous Localisation and Mapping) pipeline: - Generalised Monocular SLAM for catadioptric central cameras - Resolution of the scale problem in monocular vision - Dense RGB-D odometry - Robust place recognition - Pose-graph optimisation","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"9 1","pages":"27-29"},"PeriodicalIF":0.0,"publicationDate":"2016-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78838063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated Analysis of Orthopaedic X-ray Images based on Digital-Geometric Techniques","authors":"O. Bandyopadhyay, A. Biswas, B. Bhattacharya","doi":"10.5565/REV/ELCVIA.970","DOIUrl":"https://doi.org/10.5565/REV/ELCVIA.970","url":null,"abstract":"This thesis reports several methods for automated analysis and interpretation of bone  X -ray images. Automatic segmentation of the bone part in a digital X -ray image is a  challenging problem because of its low contrast against the surrounding flesh. In this  thesis, we propose a fully automated X -ray image segmentation technique, which is  based on a variant of entropy measure of the image. We have also analyzed the  geometric information embedded in the long-bone contour image to identify the  presence of abnormalities in the bone and perform fracture detection, fracture  classification, and bone cancer diagnosis.","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"6 1","pages":"7-9"},"PeriodicalIF":0.0,"publicationDate":"2016-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78488784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contributions to Gait Recognition Using Multiple-Views","authors":"D. López-Fernández","doi":"10.5565/REV/ELCVIA.946","DOIUrl":"https://doi.org/10.5565/REV/ELCVIA.946","url":null,"abstract":"This thesis focuses on identifying people by the way they walk. The problem of gait recognition has been addressed by using different approaches, both in the 2D and 3D domains, and using one or multiple views. However, the dependence on camera viewpoint (and therefore the dependence on the trajectory of motion) still remains an open problem. This dissertation addresses the problem of dependence on the trajectory through the use of 3D reconstructions of walking humans. The use of 3D models have several advantages that are worth mentioning. First, by the use of 3D reconstructions it is possible to exploit a greater amount of information in contrast to methods that extract descriptors from just 2D images. Second, the 3D reconstructions can be aligned along the way as if the subject had walked on a treadmill, thus providing a way to recognize people regardless the path. Three approaches are proposed in order to address the dependence on the trajectory: (1) using aligned 3D reconstructions of walking humans, (2) using unaligned 3D reconstructions of walking humans. (3) extracting a 3D description without using 3D reconstructions. Three gait descriptors are also proposed. The first focuses on describing gait by means of morphological analysis of 3D aligned volumes. The second makes use of the concept of entropy to describe the dynamics of human gait. The third aims to capture the dynamics of gait in a rotation invariant way, which makes it interesting for recognize people walking on both straight and curves path, and regardless direction changes. These approaches have been tested on the \"AVA Multi-View Dataset (AVAMVG)\" and on the \"Kyushu University 4D Gait Database (KY4D)\". Both databases are specifically designed to address the problem of dependence on the viewpoint, and therefore the dependence on the trajectory. Experimental results show that for the approach based on aligned volumetric reconstructions, the entropy-based gait descriptor achieved the best results compared to other closely related methods of the state-of-art. However, the rotation invariant gait descriptor achieves a recognition rate that overcomes the compared state-of-art methods without requiring the alignment of the 3D gait reconstructions.","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"1 1","pages":"22-23"},"PeriodicalIF":0.0,"publicationDate":"2016-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91067375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A variational approach to denoising problem","authors":"D. Thanh","doi":"10.5565/REV/ELCVIA.991","DOIUrl":"https://doi.org/10.5565/REV/ELCVIA.991","url":null,"abstract":"A digital image can be created by different digital devices, such as digital cameras, X-ray scanners, etc. In practice, such devices can give unexpected defects, for example, noise. The Gaussian noise and Poisson noise are very important, but their combination is important too. This mixed noise usually appears in electronic microscopic images, in aerospace images, etc. Our goal is to combine ROF model (for Gaussian noise removal) and modified ROF model (for Poisson noise removal) to create new model that can treat this combination effectively. Our model will treat this combination with considering proportion of noise between them.","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"53 1","pages":"19-21"},"PeriodicalIF":0.0,"publicationDate":"2016-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76300533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical and deterministic approaches for multimedia forensics","authors":"Cecilia Pasquini","doi":"10.5565/REV/ELCVIA.984","DOIUrl":"https://doi.org/10.5565/REV/ELCVIA.984","url":null,"abstract":"The increasing availability and pervasiveness of multimedia data in our society is before our very eyes. As a result of globalization and worldwide connectivity, people from all over the planet are exchanging constantly increasing amounts of images, videos, audio recordings on a daily basis. Coupled with the easy access to user-friendly editing software, this poses a number of problems related to the reliability and trustworthiness of such content, as well as its potential malevolent use. For this reason, the research field of multimedia forensics focuses on the development of forensic tools for verifying the authenticity of multimedia data. The hypothesis of pristine status of images, videos or audio tracks is called into question and can be rejected if traces of manipulation are detected with a certain degree of confidence. In this framework, studying traces left by any operation that could have been employed to process the data, either for malicious purposes or simply to improve their content or presentation, turns out to be of interest for a comprehensive forensic analysis.  The goal of this doctoral study is to contribute to the field of multimedia forensics by exploiting intrinsic statistical and deterministic properties of multimedia data.  With this respect, much work has been devoted to the study of JPEG compression traces in digital images, resulting in the development of several innovative approaches. Indeed, some of the main related research problems have been addressed and solution based on statistical properties of digital images have been proposed. In particular, the problem of identifying traces of JPEG compressions in images that have been decompressed and saved in uncompressed formats has been extensively studied, resulting in the design of novel statistical detectors. Given the enormous practical relevance, digital images in JPEG formats have also been considered. A novel method aimed at discriminating images compressed only once and more than once has been developed, and tested on a variety of images and forensic scenarios. Being the potential presence of intelligent counterfeiters ever increasingly studied, innovative counterforensic techniques to JPEG compression based on smart reconstruction strategies are proposed. Finally, we explore the possibility of defining and exploiting deterministic properties related to a certain processing operation in the forensic analysis. With this respect, we present a first approach targeted to the detection in one-dimensional data of a common data smoothing operation, the median filter. A peculiarity of this method is the ability of providing a deterministic response on the presence of median filtering traces in the data under investigation.","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"26 1","pages":"16-18"},"PeriodicalIF":0.0,"publicationDate":"2016-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84161534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anytime and Distributed Approaches for Graph Matching","authors":"Zeina Abu-Aisheh","doi":"10.5565/REV/ELCVIA.986","DOIUrl":"https://doi.org/10.5565/REV/ELCVIA.986","url":null,"abstract":"Due to the inherent genericity of graph-based representations, and thanks to the improvement of computer capacities, structural representations have become more and more popular in the field of Pattern Recognition (PR). In a graph-based representation, vertices and their attributes describe objects (or part of them) while edges represent interrelationships between the objects. Representing objects by graphs turns the problem of object comparison into graph matching (GM) where correspondences between vertices and edges of two graphs have to be found. In the domain of GM, over the last decade, Graph Edit Distance (GED) has been given a specific attention due to its flexibility to match many types of graphs. GED has been applied to a wide range of specific applications from molecule recognition to image classification. Researchers have shed light on the approximate methods that can find suboptimal solutions hopefully close to the optimal ones but the gap between optimal and suboptimal solutions has not been deeply studied yet. For that reason, in this thesis, we focus on exact GED algorithms. Unfortunately, exact GED methods have an exponential complexity. Thus, coming up with an exact GED algorithm that can be scaled up to match graphs involved in PR tasks is a great challenge. Two promising ways to cut-off computational time are search space pruning and distributed algorithms. To this end, we first propose a depth-first GED algorithm which requires less memory and search time. An evaluation of all possible solutions is performed without explicitly enumerating all of them. Candidates are discarded using an upper and lower bounds strategy. To find a trade-off between speed and optimality, we describe how to convert the proposed depth-first GED method into an anytime one that is capable of delivering a first solution very quickly. It also can find a list of improved solutions and eventually converges to the optimal solution instead of providing one and only one solution (i.e., the optimal solution). With the delight of more time, anytime methods can also reach the optimal solution. To illustrate the usage of anytime GM algorithms, we convert our depth-first GED algorithm into an anytime one. We analyze the properties of such methods to solve GM problems and consider the performance in terms of accuracy of the provided solution compared to the optimal or the best one found by a state-of-the-art methods. This thesis is also considered as a first attempt to reduce the run time of exact GED methods using parallel and distributed fashions. Two parallel and distributed GED approaches are put forward; both of them are based on the depth-first GED method. The search space is decomposed into smaller search trees which are solved independently in a parallel or a distributed manner. To benchmark the proposed GED methods, we propose not only assessing GED methods in a classification context but also evaluating them in a graph-level one (i.e., evaluating their di","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"94 1","pages":"13-15"},"PeriodicalIF":0.0,"publicationDate":"2016-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80632287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Indoor/outdoor navigation system based on possibilistic traversable area segmentation for visually impaired people","authors":"Jihen Frikha, D. Sellami, I. Kallel","doi":"10.5565/REV/ELCVIA.818","DOIUrl":"https://doi.org/10.5565/REV/ELCVIA.818","url":null,"abstract":"Autonomous collision avoidance for visually impaired people requires a specific processing for an accurate definition of traversable area. Processing of a real time image sequence for traversable area segmentation is quite mandatory. Low cost systems suggest use of poor quality cameras. However, real time low cost camera suffers from great variability of traversable area appearance at indoor as well as outdoor environments. Taking into account ambiguity affecting object and traversable area appearance induced by reflections, illumination variations, occlusions (, etc...), an accurate segmentation of traversable area in such conditions remains a challenge. Moreover, indoor and outdoor environments add additional variability to traversable areas. In this paper, we present a real-time approach for fast traversable area segmentation from image sequence recorded by a low-cost monocular camera for navigation system. Taking into account all kinds of variability in the image, we apply possibility theory for modeling information ambiguity. An efficient way of updating the traversable area model in each environment condition is to consider traversable area samples from the same processed image for building its possibility maps. Then fusing these maps allows making a fair model definition of the traversable area. Performance of the proposed system was evaluated on public databases, with indoor and outdoor environments. Experimental results show that this method is challenging leading to higher segmentation rates.","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":"61 1","pages":"60-76"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85327275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}