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Author Debora Gil; Oriol Ramos Terrades; Raquel Perez
Title Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution Type Book Chapter
Year 2021 Publication (down) Extended Abstracts GEOMVAP 2019, Trends in Mathematics 15 Abbreviated Journal
Volume 15 Issue Pages 89–93
Keywords
Abstract Abnormalities in radiomic measures correlate to genomic alterations prone to alter the outcome of personalized anti-cancer treatments. TOPiomics is a new method for the early detection of variations in tumor imaging phenotype from a topological structure in multi-view radiomic spaces.
Address
Corporate Author Thesis
Publisher Springer Nature Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM; DAG; 600.120; 600.145; 600.139 Approved no
Call Number Admin @ si @ GRP2021 Serial 3594
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Author F.Guirado; Ana Ripoll; C.Roig; Aura Hernandez-Sabate; Emilio Luque
Title Exploiting Throughput for Pipeline Execution in Streaming Image Processing Applications Type Book Chapter
Year 2006 Publication (down) Euro-Par 2006 Parallel Processing Abbreviated Journal LNCS
Volume 4128 Issue Pages 1095-1105
Keywords 12th International Euro–Par Conference
Abstract There is a large range of image processing applications that act on an input sequence of image frames that are continuously received. Throughput is a key performance measure to be optimized when execu- ting them. In this paper we propose a new task replication methodology for optimizing throughput for an image processing application in the field of medicine. The results show that by applying the proposed methodo- logy we are able to achieve the desired throughput in all cases, in such a way that the input frames can be processed at any given rate.
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Corporate Author Thesis
Publisher Springer-Verlag Berlin Heidelberg Place of Publication Dresden, Germany (European Union) Editor UAB; W, E.N.; et al.
Language Summary Language Original Title
Series Editor Series Title Lecture Notes In Computer Science Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference Euro–Par
Notes IAM Approved no
Call Number IAM @ iam @ GRR2006a Serial 1542
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Author Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva
Title On the Design of Low Redundancy Error-Correcting Output Codes Type Book Chapter
Year 2011 Publication (down) Ensembles in Machine Learning Applications Abbreviated Journal
Volume 373 Issue 2 Pages 21-38
Keywords
Abstract The classification of large number of object categories is a challenging trend in the Pattern Recognition field. In the literature, this is often addressed using an ensemble of classifiers . In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for combining classifiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a compact design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best compact ECOC code configuration. The results over several public UCI data sets and different multi-class Computer Vision problems show that the proposed methodology obtains comparable (even better) results than the state-of-the-art ECOC methodologies with far less number of dichotomizers.
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Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1860-949X ISBN 978-3-642-22909-1 Medium
Area Expedition Conference
Notes MILAB; OR;HuPBA;MV Approved no
Call Number Admin @ si @ BEB2011b Serial 1886
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Author Debora Gil; Petia Radeva
Title Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling Type Book Chapter
Year 2003 Publication (down) Energy Minimization Methods In Computer Vision And Pattern Recognition Abbreviated Journal LNCS
Volume 2683 Issue Pages 357-372
Keywords Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature
Abstract Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time.
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Corporate Author Thesis
Publisher Springer, Berlin Place of Publication Lisbon, PORTUGAL Editor Springer, B.
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 3-540-40498-8 Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GIR2003b Serial 1535
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Author Angel Sappa; Niki Aifanti; Sotiris Malassiotis; N. Grammalidis
Title Survey of 3D Human Body Representations Type Book Chapter
Year 2005 Publication (down) Encyclopedia of Information Science and Technology, 1(5):2696–2701 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number ADAS @ adas @ SAM2005a Serial 497
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Author Niki Aifanti; Angel Sappa; N. Grammalidis; Sotiris Malassiotis
Title Human Motion Tracking and Recognition Type Book Chapter
Year 2005 Publication (down) Encyclopedia of Information Science and Technology, 1(5):1355–1360 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number ADAS @ adas @ ASG2005 Serial 496
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Author Niki Aifanti; Angel Sappa; N. Grammalidis; Sotiris Malassiotis
Title Advances in Tracking and Recognition of Human Motion Type Book Chapter
Year 2009 Publication (down) Encyclopedia of Information Science and Technology Abbreviated Journal
Volume I Issue 2nd edition Pages 65–71
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ ASG2009 Serial 1143
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Author C. Alejandro Parraga
Title Color Vision, Computational Methods for Type Book Chapter
Year 2014 Publication (down) Encyclopedia of Computational Neuroscience Abbreviated Journal
Volume Issue Pages 1-11
Keywords Color computational vision; Computational neuroscience of color
Abstract The study of color vision has been aided by a whole battery of computational methods that attempt to describe the mechanisms that lead to our perception of colors in terms of the information-processing properties of the visual system. Their scope is highly interdisciplinary, linking apparently dissimilar disciplines such as mathematics, physics, computer science, neuroscience, cognitive science, and psychology. Since the sensation of color is a feature of our brains, computational approaches usually include biological features of neural systems in their descriptions, from retinal light-receptor interaction to subcortical color opponency, cortical signal decoding, and color categorization. They produce hypotheses that are usually tested by behavioral or psychophysical experiments.
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Corporate Author Thesis
Publisher Springer-Verlag Berlin Heidelberg Place of Publication Editor Dieter Jaeger; Ranu Jung
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-4614-7320-6 Medium
Area Expedition Conference
Notes CIC; 600.074 Approved no
Call Number Admin @ si @ Par2014 Serial 2512
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Author Fadi Dornaika; Bogdan Raducanu
Title Facial Expression Recognition for HCI Applications Type Book Chapter
Year 2008 Publication (down) Encyclopedia of Artificial Intelligence Abbreviated Journal
Volume II Issue Pages 625–631
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Abstract
Address
Corporate Author Thesis
Publisher IGI–Global Publisher Place of Publication Editor Rabuñal
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ DoR2008c Serial 1034
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Author Fadi Dornaika; Bogdan Raducanu; Alireza Bosaghzadeh
Title Facial expression recognition based on multi observations with application to social robotics Type Book Chapter
Year 2015 Publication (down) Emotional and Facial Expressions: Recognition, Developmental Differences and Social Importance Abbreviated Journal
Volume Issue Pages 153-166
Keywords
Abstract Human-robot interaction is a hot topic nowadays in the social robotics
community. One crucial aspect is represented by the affective communication
which comes encoded through the facial expressions. In this chapter, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, viewand texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial
expression.
Address
Corporate Author Thesis
Publisher Nova Science publishers Place of Publication Editor Bruce Flores
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes LAMP; Approved no
Call Number Admin @ si @ DRB2015 Serial 2720
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Author Antonio Lopez; Jiaolong Xu; Jose Luis Gomez; David Vazquez; German Ros
Title From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example Type Book Chapter
Year 2017 Publication (down) Domain Adaptation in Computer Vision Applications Abbreviated Journal
Volume Issue 13 Pages 243-258
Keywords Domain Adaptation
Abstract Supervised learning tends to produce more accurate classifiers than unsupervised learning in general. This implies that training data is preferred with annotations. When addressing visual perception challenges, such as localizing certain object classes within an image, the learning of the involved classifiers turns out to be a practical bottleneck. The reason is that, at least, we have to frame object examples with bounding boxes in thousands of images. A priori, the more complex the model is regarding its number of parameters, the more annotated examples are required. This annotation task is performed by human oracles, which ends up in inaccuracies and errors in the annotations (aka ground truth) since the task is inherently very cumbersome and sometimes ambiguous. As an alternative we have pioneered the use of virtual worlds for collecting such annotations automatically and with high precision. However, since the models learned with virtual data must operate in the real world, we still need to perform domain adaptation (DA). In this chapter we revisit the DA of a deformable part-based model (DPM) as an exemplifying case of virtual- to-real-world DA. As a use case, we address the challenge of vehicle detection for driver assistance, using different publicly available virtual-world data. While doing so, we investigate questions such as: how does the domain gap behave due to virtual-vs-real data with respect to dominant object appearance per domain, as well as the role of photo-realism in the virtual world.
Address
Corporate Author Thesis
Publisher Springer Place of Publication Editor Gabriela Csurka
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS; 600.085; 601.223; 600.076; 600.118 Approved no
Call Number ADAS @ adas @ LXG2017 Serial 2872
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Author German Ros; Laura Sellart; Gabriel Villalonga; Elias Maidanik; Francisco Molero; Marc Garcia; Adriana Cedeño; Francisco Perez; Didier Ramirez; Eduardo Escobar; Jose Luis Gomez; David Vazquez; Antonio Lopez
Title Semantic Segmentation of Urban Scenes via Domain Adaptation of SYNTHIA Type Book Chapter
Year 2017 Publication (down) Domain Adaptation in Computer Vision Applications Abbreviated Journal
Volume 12 Issue Pages 227-241
Keywords SYNTHIA; Virtual worlds; Autonomous Driving
Abstract Vision-based semantic segmentation in urban scenarios is a key functionality for autonomous driving. Recent revolutionary results of deep convolutional neural networks (DCNNs) foreshadow the advent of reliable classifiers to perform such visual tasks. However, DCNNs require learning of many parameters from raw images; thus, having a sufficient amount of diverse images with class annotations is needed. These annotations are obtained via cumbersome, human labour which is particularly challenging for semantic segmentation since pixel-level annotations are required. In this chapter, we propose to use a combination of a virtual world to automatically generate realistic synthetic images with pixel-level annotations, and domain adaptation to transfer the models learnt to correctly operate in real scenarios. We address the question of how useful synthetic data can be for semantic segmentation – in particular, when using a DCNN paradigm. In order to answer this question we have generated a synthetic collection of diverse urban images, named SYNTHIA, with automatically generated class annotations and object identifiers. We use SYNTHIA in combination with publicly available real-world urban images with manually provided annotations. Then, we conduct experiments with DCNNs that show that combining SYNTHIA with simple domain adaptation techniques in the training stage significantly improves performance on semantic segmentation.
Address
Corporate Author Thesis
Publisher Springer Place of Publication Editor Gabriela Csurka
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS; 600.085; 600.082; 600.076; 600.118 Approved no
Call Number ADAS @ adas @ RSV2017 Serial 2882
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Author Ernest Valveny; Philippe Dosch
Title Performance Evaluation of Symbol Recognition Type Book Chapter
Year 2004 Publication (down) Document Analysis Systems Abbreviated Journal LNCS
Volume 3163 Issue Pages 354–365
Keywords
Abstract
Address Springer-Verlag
Corporate Author Thesis
Publisher Place of Publication Editor S. Marinai, A. Dengel (Eds.),
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 3-540-23060-2 Medium
Area Expedition Conference
Notes DAG Approved no
Call Number DAG @ dag @ VaD2004a Serial 502
Permanent link to this record
 
 
Author Josep Llados
Title Advances in Graphics Recognition Type Book Chapter
Year 2007 Publication (down) Digital Document Processing, Major Directions and Recent Advances, Advances in Pattern Recognition, B.B. Chaudhuri, ed., 281–304 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Springer London
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG Approved no
Call Number DAG @ dag @ Lla2007 Serial 780
Permanent link to this record
 
 
Author Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez
Title Trajectory-Based Abnormality Categorization for Learning Route Patterns in Surveillance Type Book Chapter
Year 2012 Publication (down) Detection and Identification of Rare Audiovisual Cues, Studies in Computational Intelligence Abbreviated Journal
Volume 384 Issue 3 Pages 87-95
Keywords
Abstract The recognition of abnormal behaviors in video sequences has raised as a hot topic in video understanding research. Particularly, an important challenge resides on automatically detecting abnormality. However, there is no convention about the types of anomalies that training data should derive. In surveillance, these are typically detected when new observations differ substantially from observed, previously learned behavior models, which represent normality. This paper focuses on properly defining anomalies within trajectory analysis: we propose a hierarchical representation conformed by Soft, Intermediate, and Hard Anomaly, which are identified from the extent and nature of deviation from learned models. Towards this end, a novel Gaussian Mixture Model representation of learned route patterns creates a probabilistic map of the image plane, which is applied to detect and classify anomalies in real-time. Our method overcomes limitations of similar existing approaches, and performs correctly even when the tracking is affected by different sources of noise. The reliability of our approach is demonstrated experimentally.
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Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1860-949X ISBN 978-3-642-24033-1 Medium
Area Expedition Conference
Notes ISE Approved no
Call Number Admin @ si @ BFR2012 Serial 2062
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