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Author | Ariel Amato; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez | ||||
Title | Robust Real-Time Background Subtraction Based on Local Neighborhood Patterns | Type | Journal Article | ||
Year | 2010 | Publication | EURASIP Journal on Advances in Signal Processing | Abbreviated Journal | EURASIPJ |
Volume | Issue | Pages | 7 | ||
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Abstract | Article ID 901205
This paper describes an efficient background subtraction technique for detecting moving objects. The proposed approach is able to overcome difficulties like illumination changes and moving shadows. Our method introduces two discriminative features based on angular and modular patterns, which are formed by similarity measurement between two sets of RGB color vectors: one belonging to the background image and the other to the current image. We show how these patterns are used to improve foreground detection in the presence of moving shadows and in the case when there are strong similarities in color between background and foreground pixels. Experimental results over a collection of public and own datasets of real image sequences demonstrate that the proposed technique achieves a superior performance compared with state-of-the-art methods. Furthermore, both the low computational and space complexities make the presented algorithm feasible for real-time applications. |
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ISSN | 1110-8657 | ISBN | Medium | ||
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Notes | ISE | Approved | no | ||
Call Number | ISE @ ise @ AMR2010 | Serial | 1463 | ||
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Author | Enrique Cabello; Cristina Conde; Angel Serrano; Licesio Rodriguez; David Vazquez | ||||
Title | Empleo de sistemas biométricos para el reconocimiento de personas en aeropuertos | Type | Journal Article | ||
Year | 2006 | Publication | Instituto Universitario de Investigación sobre Seguridad Interior (IUSI 2006) | Abbreviated Journal | |
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Keywords | Surveillance; Face detection; Face recognition | ||||
Abstract | El presente proyecto se desarrolló a lo largo del año 2005, probando un prototipo de un sistema de verificación facial con imágenes extraídas de las cámaras de video vigilancia del aeropuerto de Barajas. Se diseñaron varios experimentos, agrupados en dos clases. En el primer tipo, el sistema es entrenado con imágenes obtenidas en condiciones de laboratorio y luego probado con imágenes extraídas de las cámaras de video vigilancia del aeropuerto de Barajas. En el segundo caso, tanto las imágenes de entrenamiento como las de prueba corresponden a imágenes extraídas de Barajas. Se ha desarrollado un sistema completo, que incluye adquisición y digitalización de las imágenes, localización y recorte de las caras en escena, verificación de sujetos y obtención de resultados. Los resultados muestran, que, en general, un sistema de verificación facial basado en imágenes puede ser una ayuda a un operario que deba estar vigilando amplias zonas. | ||||
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Notes | invisible;ADAS | Approved | no | ||
Call Number | ADAS @ adas @ CCS2006a | Serial | 1672 | ||
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Author | Ole Larsen; Petia Radeva; Enric Marti | ||||
Title | Bounds on the optimal elasticity parameters for a snake | Type | Journal Article | ||
Year | 1995 | Publication | Image Analysis and Processing | Abbreviated Journal | |
Volume | Issue | Pages | 37-42 | ||
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Abstract | This paper develops a formalism by which an estimate for the upper and lower bounds for the elasticity parameters for a snake can be obtained. Objects different in size and shape give rise to different bounds. The bounds can be obtained based on an analysis of the shape of the object of interest. Experiments on synthetic images show a good correlation between the estimated behaviour of the snake and the one actually observed. Experiments on real X-ray images show that the parameters for optimal segmentation lie within the estimated bounds. | ||||
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Notes | MILAB;IAM | Approved | no | ||
Call Number | IAM @ iam @ LRM1995a | Serial | 1559 | ||
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Author | Josep Llados; Enric Marti | ||||
Title | Graph-edit algorithms for hand-drawn graphical document recognition and their automatic introduction | Type | Journal Article | ||
Year | 1999 | Publication | Machine Graphics & Vision journal, special issue on Graph transformation | Abbreviated Journal | |
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Notes | DAG;IAM | Approved | no | ||
Call Number | IAM @ iam @ LIM1999c | Serial | 1569 | ||
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Author | Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; C. Garcia; R. Villuendas; Vicente del Valle; Debora Gil; Petia Radeva | ||||
Title | Reconstruction of a spatio-temporal model of the intima layer from intravascular ultrasound sequences | Type | Journal Article | ||
Year | 2003 | Publication | European Heart Journal | Abbreviated Journal | |
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Area | Expedition | Conference | ESC Congress | ||
Notes | IAM;MILAB | Approved | no | ||
Call Number | IAM @ iam @ RMF2003c | Serial | 1641 | ||
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Author | Wenjuan Gong; Jordi Gonzalez; Xavier Roca | ||||
Title | Human Action Recognition based on Estimated Weak Poses | Type | Journal Article | ||
Year | 2012 | Publication | EURASIP Journal on Advances in Signal Processing | Abbreviated Journal | EURASIPJ |
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Abstract | We present a novel method for human action recognition (HAR) based on estimated poses from image sequences. We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose. With predicted poses from image features, we map the problem from image feature space to pose space, where a Bag of Poses (BOP) model is learned for the final goal of HAR. The BOP model is a modified version of the classical bag of words pipeline by building the vocabulary based on the most representative weak poses for a given action. Compared with the standard k-means clustering, our vocabulary selection criteria is proven to be more efficient and robust against the inherent challenges of action recognition. Moreover, since for action recognition the ordering of the poses is discriminative, the BOP model incorporates temporal information: in essence, groups of consecutive poses are considered together when computing the vocabulary and assignment. We tested our method on two well-known datasets: HumanEva and IXMAS, to demonstrate that weak poses aid to improve action recognition accuracies. The proposed method is scene-independent and is comparable with the state-of-art method. | ||||
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Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ GGR2012 | Serial | 2003 | ||
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Author | Stefan Ameling; Stephan Wirth; Dietrich Paulus; Gerard Lacey; Fernando Vilariño | ||||
Title | Texture-based Polyp Detection in Colonoscopy | Type | Journal Article | ||
Year | 2009 | Publication | Proc. BILDVERARBEITUNG FÜR DIE MEDIZIN | Abbreviated Journal | |
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Area | 800 | Expedition | Conference | ||
Notes | MV;SIAI | Approved | no | ||
Call Number | fernando @ fernando @ | Serial | 2428 | ||
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Author | Wenjuan Gong; W.Zhang; Jordi Gonzalez; Y.Ren; Z.Li | ||||
Title | Enhanced Asymmetric Bilinear Model for Face Recognition | Type | Journal Article | ||
Year | 2015 | Publication | International Journal of Distributed Sensor Networks | Abbreviated Journal | IJDSN |
Volume | Issue | Pages | Article ID 218514 | ||
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Abstract | Bilinear models have been successfully applied to separate two factors, for example, pose variances and different identities in face recognition problems. Asymmetric model is a type of bilinear model which models a system in the most concise way. But seldom there are works exploring the applications of asymmetric bilinear model on face recognition problem with illumination changes. In this work, we propose enhanced asymmetric model for illumination-robust face recognition. Instead of initializing the factor probabilities randomly, we initialize them with nearest neighbor method and optimize them for the test data. Above that, we update the factor model to be identified. We validate the proposed method on a designed data sample and extended Yale B dataset. The experiment results show that the enhanced asymmetric models give promising results and good recognition accuracies. | ||||
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Notes | ISE; 600.063; 600.078 | Approved | no | ||
Call Number | Admin @ si @ GZG2015 | Serial | 2592 | ||
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Author | Manuel Graña; Bogdan Raducanu | ||||
Title | Special Issue on Bioinspired and knowledge based techniques and applications | Type | Journal Article | ||
Year | 2015 | Publication | Neurocomputing | Abbreviated Journal | NEUCOM |
Volume | Issue | Pages | 1-3 | ||
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Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ GrR2015 | Serial | 2598 | ||
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Author | Onur Ferhat; Fernando Vilariño | ||||
Title | Low Cost Eye Tracking: The Current Panorama | Type | Journal Article | ||
Year | 2016 | Publication | Computational Intelligence and Neuroscience | Abbreviated Journal | CIN |
Volume | Issue | Pages | Article ID 8680541 | ||
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Abstract | Despite the availability of accurate, commercial gaze tracker devices working with infrared (IR) technology, visible light gaze tracking constitutes an interesting alternative by allowing scalability and removing hardware requirements. Over the last years, this field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration strategies, head pose invariance, and gaze estimation techniques. We also provide information on related aspects of research such as public datasets to test against, open source projects to build upon, and gaze tracking services to directly use in applications. With all this information, we aim to provide the contemporary and future researchers with a map detailing previously explored ideas and the required tools. | ||||
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Notes | MV; 605.103; 600.047; 600.097;SIAI | Approved | no | ||
Call Number | Admin @ si @ FeV2016 | Serial | 2744 | ||
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Author | Pau Rodriguez; Guillem Cucurull; Jordi Gonzalez; Josep M. Gonfaus; Kamal Nasrollahi; Thomas B. Moeslund; Xavier Roca | ||||
Title | Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification | Type | Journal Article | ||
Year | 2017 | Publication | IEEE Transactions on cybernetics | Abbreviated Journal | Cyber |
Volume | Issue | Pages | 1-11 | ||
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Abstract | Pain is an unpleasant feeling that has been shown to be an important factor for the recovery of patients. Since this is costly in human resources and difficult to do objectively, there is the need for automatic systems to measure it. In this paper, contrary to current state-of-the-art techniques in pain assessment, which are based on facial features only, we suggest that the performance can be enhanced by feeding the raw frames to deep learning models, outperforming the latest state-of-the-art results while also directly facing the problem of imbalanced data. As a baseline, our approach first uses convolutional neural networks (CNNs) to learn facial features from VGG_Faces, which are then linked to a long short-term memory to exploit the temporal relation between video frames. We further compare the performances of using the so popular schema based on the canonically normalized appearance versus taking into account the whole image. As a result, we outperform current state-of-the-art area under the curve performance in the UNBC-McMaster Shoulder Pain Expression Archive Database. In addition, to evaluate the generalization properties of our proposed methodology on facial motion recognition, we also report competitive results in the Cohn Kanade+ facial expression database. | ||||
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Notes | ISE; 600.119; 600.098 | Approved | no | ||
Call Number | Admin @ si @ RCG2017a | Serial | 2926 | ||
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Author | David Vazquez; Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Antonio Lopez; Adriana Romero; Michal Drozdzal; Aaron Courville | ||||
Title | A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images | Type | Journal Article | ||
Year | 2017 | Publication | Journal of Healthcare Engineering | Abbreviated Journal | JHCE |
Volume | Issue | Pages | 2040-2295 | ||
Keywords | Colonoscopy images; Deep Learning; Semantic Segmentation | ||||
Abstract | Colorectal cancer (CRC) is the third cause of cancer death world-wide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss- rate and inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing Decision Support Systems (DSS) aim- ing to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image segmentation, with the hope of establishing a new strong benchmark for colonoscopy image analysis research. The proposed dataset consists of 4 relevant classes to inspect the endolumninal scene, tar- geting different clinical needs. Together with the dataset and taking advantage of advances in semantic segmentation literature, we provide new baselines by training standard fully convolutional networks (FCN). We perform a compar- ative study to show that FCN significantly outperform, without any further post-processing, prior results in endoluminal scene segmentation, especially with respect to polyp segmentation and localization. | ||||
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Notes | ADAS; MV; 600.075; 600.085; 600.076; 601.281; 600.118 | Approved | no | ||
Call Number | VBS2017b | Serial | 2940 | ||
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Author | Marta Diez-Ferrer; Debora Gil; Elena Carreño; Susana Padrones; Samantha Aso; Vanesa Vicens; Noelia Cubero de Frutos; Rosa Lopez Lisbona; Carles Sanchez; Agnes Borras; Antoni Rosell | ||||
Title | Positive Airway Pressure-Enhanced CT to Improve Virtual Bronchoscopic Navigation | Type | Journal Article | ||
Year | 2017 | Publication | European Respiratory Journal | Abbreviated Journal | ERJ |
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Notes | IAM | Approved | no | ||
Call Number | Admin @ si @ DGC2017b | Serial | 3632 | ||
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Author | F. Javier Sanchez; Jorge Bernal; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach | ||||
Title | Bright spot regions segmentation and classification for specular highlights detection in colonoscopy videos | Type | Journal Article | ||
Year | 2017 | Publication | Machine Vision and Applications | Abbreviated Journal | MVAP |
Volume | Issue | Pages | 1-20 | ||
Keywords | Specular highlights; bright spot regions segmentation; region classification; colonoscopy | ||||
Abstract | A novel specular highlights detection method in colonoscopy videos is presented. The method is based on a model of appearance dening specular
highlights as bright spots which are highly contrasted with respect to adjacent regions. Our approach proposes two stages; segmentation, and then classication of bright spot regions. The former denes a set of candidate regions obtained through a region growing process with local maxima as initial region seeds. This process creates a tree structure which keeps track, at each growing iteration, of the region frontier contrast; nal regions provided depend on restrictions over contrast value. Non-specular regions are ltered through a classication stage performed by a linear SVM classier using model-based features from each region. We introduce a new validation database with more than 25; 000 regions along with their corresponding pixel-wise annotations. We perform a comparative study against other approaches. Results show that our method is superior to other approaches, with our segmented regions being closer to actual specular regions in the image. Finally, we also present how our methodology can also be used to obtain an accurate prediction of polyp histology. |
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Notes | MV; 600.096; 600.175 | Approved | no | ||
Call Number | Admin @ si @ SBS2017 | Serial | 2975 | ||
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Author | Domicele Jonauskaite; Nele Dael; C. Alejandro Parraga; Laetitia Chevre; Alejandro Garcia Sanchez; Christine Mohr | ||||
Title | Stripping #The Dress: The importance of contextual information on inter-individual differences in colour perception | Type | Journal Article | ||
Year | 2018 | Publication | Psychological Research | Abbreviated Journal | PSYCHO R |
Volume | Issue | Pages | 1-15 | ||
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Abstract | In 2015, a picture of a Dress (henceforth the Dress) triggered popular and scientific interest; some reported seeing the Dress in white and gold (W&G) and others in blue and black (B&B). We aimed to describe the phenomenon and investigate the role of contextualization. Few days after the Dress had appeared on the Internet, we projected it to 240 students on two large screens in the classroom. Participants reported seeing the Dress in B&B (48%), W&G (38%), or blue and brown (B&Br; 7%). Amongst numerous socio-demographic variables, we only observed that W&G viewers were most likely to have always seen the Dress as W&G. In the laboratory, we tested how much contextual information is necessary for the phenomenon to occur. Fifty-seven participants selected colours most precisely matching predominant colours of parts or the full Dress. We presented, in this order, small squares (a), vertical strips (b), and the full Dress (c). We found that (1) B&B, B&Br, and W&G viewers had selected colours differing in lightness and chroma levels for contextualized images only (b, c conditions) and hue for fully contextualized condition only (c) and (2) B&B viewers selected colours most closely matching displayed colours of the Dress. Thus, the Dress phenomenon emerges due to inter-individual differences in subjectively perceived lightness, chroma, and hue, at least when all aspects of the picture need to be integrated. Our results support the previous conclusions that contextual information is key to colour perception; it should be important to understand how this actually happens. | ||||
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Notes | NEUROBIT; no proj | Approved | no | ||
Call Number | Admin @ si @ JDP2018 | Serial | 3149 | ||
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