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Author (up) Simeon Petkov; Adriana Romero; Xavier Carrillo; Petia Radeva; Carlo Gatta
Title Robust and accurate diaphragm border detection in cardiac X-Ray angiographies Type Conference Article
Year 2012 Publication Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges Abbreviated Journal
Volume 7746 Issue Pages 225-234
Keywords
Abstract Workshop STACOM, dins del MICCAI
X-ray angiography is the most common imaging modality employed in the diagnosis of coronary diseases prior to or during a catheter-based intervention. The analysis of the patient X-Ray sequence can provide useful information about the degree of arterial stenosis, the myocardial perfusion and other clinical parameters. If the sequence has been acquired to evaluate the perfusion grade, the opacity due to the diaphragm could potentially hinder any kind of visual inspection and make more difficult a computer aided measurements. In this paper we propose an accurate and robust method to automatically identify the diaphragm border in each frame. Quantitative evaluation on a set of 11 sequences shows that the proposed algorithm outperforms previous methods.
Address Nice, France
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-36960-5 Medium
Area Expedition Conference STACOM
Notes MILAB Approved no
Call Number Admin @ si @ PRC2012 Serial 2028
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Author (up) Simone Balocco; Carlo Gatta; Marina Alberti; Xavier Carrillo; Juan Rigla; Petia Radeva
Title Relation between plaque type, plaque thickness, blood shear stress and plaque stress in coronary arteries assessed by X-ray Angiography and Intravascular Ultrasound Type Journal Article
Year 2012 Publication Medical Physics Abbreviated Journal MEDPHYS
Volume 39 Issue 12 Pages 7430-7445
Keywords
Abstract PMID 23231293
PURPOSE:
Atheromatic plaque progression is affected, among others phenomena, by biomechanical, biochemical, and physiological factors. In this paper, the authors introduce a novel framework able to provide both morphological (vessel radius, plaque thickness, and type) and biomechanical (wall shear stress and Von Mises stress) indices of coronary arteries.
METHODS:
First, the approach reconstructs the three-dimensional morphology of the vessel from intravascular ultrasound (IVUS) and Angiographic sequences, requiring minimal user interaction. Then, a computational pipeline allows to automatically assess fluid-dynamic and mechanical indices. Ten coronary arteries are analyzed illustrating the capabilities of the tool and confirming previous technical and clinical observations.
RESULTS:
The relations between the arterial indices obtained by IVUS measurement and simulations have been quantitatively analyzed along the whole surface of the artery, extending the analysis of the coronary arteries shown in previous state of the art studies. Additionally, for the first time in the literature, the framework allows the computation of the membrane stresses using a simplified mechanical model of the arterial wall.
CONCLUSIONS:
Circumferentially (within a given frame), statistical analysis shows an inverse relation between the wall shear stress and the plaque thickness. At the global level (comparing a frame within the entire vessel), it is observed that heavy plaque accumulations are in general calcified and are located in the areas of the vessel having high wall shear stress. Finally, in their experiments the inverse proportionality between fluid and structural stresses is observed.
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 MILAB Approved no
Call Number Admin @ si @BGA2012 Serial 2170
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Author (up) Sophie Wuerger; Kaida Xiao; Dimitris Mylonas; Q. Huang; Dimosthenis Karatzas; Galina Paramei
Title Blue green color categorization in mandarin english speakers Type Journal Article
Year 2012 Publication Journal of the Optical Society of America A Abbreviated Journal JOSA A
Volume 29 Issue 2 Pages A102-A1207
Keywords
Abstract Observers are faster to detect a target among a set of distracters if the targets and distracters come from different color categories. This cross-boundary advantage seems to be limited to the right visual field, which is consistent with the dominance of the left hemisphere for language processing [Gilbert et al., Proc. Natl. Acad. Sci. USA 103, 489 (2006)]. Here we study whether a similar visual field advantage is found in the color identification task in speakers of Mandarin, a language that uses a logographic system. Forty late Mandarin-English bilinguals performed a blue-green color categorization task, in a blocked design, in their first language (L1: Mandarin) or second language (L2: English). Eleven color singletons ranging from blue to green were presented for 160 ms, randomly in the left visual field (LVF) or right visual field (RVF). Color boundary and reaction times (RTs) at the color boundary were estimated in L1 and L2, for both visual fields. We found that the color boundary did not differ between the languages; RTs at the color boundary, however, were on average more than 100 ms shorter in the English compared to the Mandarin sessions, but only when the stimuli were presented in the RVF. The finding may be explained by the script nature of the two languages: Mandarin logographic characters are analyzed visuospatially in the right hemisphere, which conceivably facilitates identification of color presented to the LVF.
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 DAG Approved no
Call Number Admin @ si @ WXM2012 Serial 2007
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Author (up) Susana Alvarez
Title Revisión de la teoría de los Textons Enfoque computacional en color Type Book Whole
Year 2012 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract El color y la textura son dos estímulos visuales importantes para la interpretación de las imágenes. La definición de descriptores computacionales que combinan estas dos características es aún un problema abierto. La dificultad se deriva esencialmente de la propia naturaleza de ambas, mientras que la textura es una propiedad de una región, el color es una propiedad de un punto.

Hasta ahora se han utilizado tres los tipos de aproximaciones para la combinación, (a) se describe la textura directamente en cada uno de los canales color, (b) se describen textura y color por separado y se combinan al final, y (c) la combinación se realiza con técnicas de aprendizaje automático. Considerando que este problema se resuelve en el sistema visual humano en niveles muy tempranos, en esta tesis se propone estudiar el problema a partir de la implementación directa de una teoría perceptual, la teoría de los textons, y explorar así su extensión a color.

Puesto que la teoría de los textons se basa en la descripción de la textura a partir de las densidades de los atributos locales, esto se adapta perfectamente al marco de trabajo de los descriptores holísticos (bag-of-words). Se han estudiado diversos descriptores basados en diferentes espacios de textons, y diferentes representaciones de las imágenes. Asimismo se ha estudiado la viabilidad de estos descriptores en una representación conceptual de nivel intermedio.

Los descriptores propuestos han demostrado ser muy eficientes en aplicaciones de recuperación y clasificación de imágenes, presentando ventajas en la generación de vocabularios. Los vocabularios se obtienen cuantificando directamente espacios de baja dimensión y la perceptualidad de estos espacios permite asociar semántica de bajo nivel a las palabras visuales. El estudio de los resultados permite concluir que si bien la aproximación holística es muy eficiente, la introducción de co-ocurrencia espacial de las propiedades de forma y color de los blobs de la imagen es un elemento clave para su combinación, hecho que no contradice las evidencias en percepción
Address
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Maria Vanrell;Xavier Otazu
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes CIC Approved no
Call Number Alv2012b Serial 2216
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Author (up) Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu
Title Low-dimensional and Comprehensive Color Texture Description Type Journal Article
Year 2012 Publication Computer Vision and Image Understanding Abbreviated Journal CVIU
Volume 116 Issue I Pages 54-67
Keywords
Abstract Image retrieval can be dealt by combining standard descriptors, such as those of MPEG-7, which are defined independently for each visual cue (e.g. SCD or CLD for Color, HTD for texture or EHD for edges).
A common problem is to combine similarities coming from descriptors representing different concepts in different spaces. In this paper we propose a color texture description that bypasses this problem from its inherent definition. It is based on a low dimensional space with 6 perceptual axes. Texture is described in a 3D space derived from a direct implementation of the original Julesz’s Texton theory and color is described in a 3D perceptual space. This early fusion through the blob concept in these two bounded spaces avoids the problem and allows us to derive a sparse color-texture descriptor that achieves similar performance compared to MPEG-7 in image retrieval. Moreover, our descriptor presents comprehensive qualities since it can also be applied either in segmentation or browsing: (a) a dense image representation is defined from the descriptor showing a reasonable performance in locating texture patterns included in complex images; and (b) a vocabulary of basic terms is derived to build an intermediate level descriptor in natural language improving browsing by bridging semantic gap
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 1077-3142 ISBN Medium
Area Expedition Conference
Notes CAT;CIC Approved no
Call Number Admin @ si @ ASV2012 Serial 1827
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Author (up) Susana Alvarez; Maria Vanrell
Title Texton theory revisited: a bag-of-words approach to combine textons Type Journal Article
Year 2012 Publication Pattern Recognition Abbreviated Journal PR
Volume 45 Issue 12 Pages 4312-4325
Keywords
Abstract The aim of this paper is to revisit an old theory of texture perception and
update its computational implementation by extending it to colour. With this in mind we try to capture the optimality of perceptual systems. This is achieved in the proposed approach by sharing well-known early stages of the visual processes and extracting low-dimensional features that perfectly encode adequate properties for a large variety of textures without needing further learning stages. We propose several descriptors in a bag-of-words framework that are derived from different quantisation models on to the feature spaces. Our perceptual features are directly given by the shape and colour attributes of image blobs, which are the textons. In this way we avoid learning visual words and directly build the vocabularies on these lowdimensionaltexton spaces. Main differences between proposed descriptors rely on how co-occurrence of blob attributes is represented in the vocabularies. Our approach overcomes current state-of-art in colour texture description which is proved in several experiments on large texture datasets.
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 0031-3203 ISBN Medium
Area Expedition Conference
Notes CIC Approved no
Call Number Admin @ si @ AlV2012a Serial 2130
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Author (up) Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades
Title Text/graphic separation using a sparse representation with multi-learned dictionaries Type Conference Article
Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages
Keywords Graphics Recognition; Layout Analysis; Document Understandin
Abstract In this paper, we propose a new approach to extract text regions from graphical documents. In our method, we first empirically construct two sequences of learned dictionaries for the text and graphical parts respectively. Then, we compute the sparse representations of all different sizes and non-overlapped document patches in these learned dictionaries. Based on these representations, each patch can be classified into the text or graphic category by comparing its reconstruction errors. Same-sized patches in one category are then merged together to define the corresponding text or graphic layers which are combined to createfinal text/graphic layer. Finally, in a post-processing step, text regions are further filtered out by using some learned thresholds.
Address Tsukuba
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 ICPR
Notes DAG Approved no
Call Number Admin @ si @ DTR2012a Serial 2135
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Author (up) Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades
Title Noise suppression over bi-level graphical documents using a sparse representation Type Conference Article
Year 2012 Publication Colloque International Francophone sur l'Écrit et le Document Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Bordeaux
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 CIFED
Notes DAG Approved no
Call Number Admin @ si @ DTR2012b Serial 2136
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Author (up) Theo Gevers; Arjan Gijsenij; Joost Van de Weijer; J.M. Geusebroek
Title Color in Computer Vision: Fundamentals and Applications Type Book Whole
Year 2012 Publication Color in Computer Vision: Fundamentals and Applications Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher The Wiley-IS&T Series in Imaging Science and Technology Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-0-470-89084-4 Medium
Area Expedition Conference
Notes ALTRES;ISE Approved no
Call Number Admin @ si @ GGG2012a Serial 2068
Permanent link to this record
 
 
Author (up) Volkmar Frinken; Alicia Fornes; Josep Llados; Jean-Marc Ogier
Title Bidirectional Language Model for Handwriting Recognition Type Conference Article
Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal
Volume 7626 Issue Pages 611-619
Keywords
Abstract In order to improve the results of automatically recognized handwritten text, information about the language is commonly included in the recognition process. A common approach is to represent a text line as a sequence. It is processed in one direction and the language information via n-grams is directly included in the decoding. This approach, however, only uses context on one side to estimate a word’s probability. Therefore, we propose a bidirectional recognition in this paper, using distinct forward and a backward language models. By combining decoding hypotheses from both directions, we achieve a significant increase in recognition accuracy for the off-line writer independent handwriting recognition task. Both language models are of the same type and can be estimated on the same corpus. Hence, the increase in recognition accuracy comes without any additional need for training data or language modeling complexity.
Address Japan
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-34165-6 Medium
Area Expedition Conference SSPR&SPR
Notes DAG Approved no
Call Number Admin @ si @ FFL2012 Serial 2057
Permanent link to this record
 
 
Author (up) Volkmar Frinken; Francisco Zamora; Salvador España; Maria Jose Castro; Andreas Fischer; Horst Bunke
Title Long-Short Term Memory Neural Networks Language Modeling for Handwriting Recognition Type Conference Article
Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 701-704
Keywords
Abstract Unconstrained handwritten text recognition systems maximize the combination of two separate probability scores. The first one is the observation probability that indicates how well the returned word sequence matches the input image. The second score is the probability that reflects how likely a word sequence is according to a language model. Current state-of-the-art recognition systems use statistical language models in form of bigram word probabilities. This paper proposes to model the target language by means of a recurrent neural network with long-short term memory cells. Because the network is recurrent, the considered context is not limited to a fixed size especially as the memory cells are designed to deal with long-term dependencies. In a set of experiments conducted on the IAM off-line database we show the superiority of the proposed language model over statistical n-gram models.
Address Tsukuba Science City, Japan
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 1051-4651 ISBN 978-1-4673-2216-4 Medium
Area Expedition Conference ICPR
Notes DAG Approved no
Call Number Admin @ si @ FZE2012 Serial 2052
Permanent link to this record
 
 
Author (up) Volkmar Frinken; Markus Baumgartner; Andreas Fischer; Horst Bunke
Title Semi-Supervised Learning for Cursive Handwriting Recognition using Keyword Spotting Type Conference Article
Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 49-54
Keywords
Abstract State-of-the-art handwriting recognition systems are learning-based systems that require large sets of training data. The creation of training data, and consequently the creation of a well-performing recognition system, requires therefore a substantial amount of human work. This can be reduced with semi-supervised learning, which uses unlabeled text lines for training as well. Current approaches estimate the correct transcription of the unlabeled data via handwriting recognition which is not only extremely demanding as far as computational costs are concerned but also requires a good model of the target language. In this paper, we propose a different approach that makes use of keyword spotting, which is significantly faster and does not need any language model. In a set of experiments we demonstrate its superiority over existing approaches.
Address Bari, Italy
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 10.1109/ICFHR.2012.268 ISBN 978-1-4673-2262-1 Medium
Area Expedition Conference ICFHR
Notes DAG Approved no
Call Number Admin @ si @ FBF2012 Serial 2055
Permanent link to this record
 
 
Author (up) Wenjuan Gong; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca
Title A New Image Dataset on Human Interactions Type Conference Article
Year 2012 Publication 7th Conference on Articulated Motion and Deformable Objects Abbreviated Journal
Volume 7378 Issue Pages 204-209
Keywords
Abstract This article describes a new collection of still image dataset which are dedicated to interactions between people. Human action recognition from still images have been a hot topic recently, but most of them are actions performed by a single person, like running, walking, riding bikes, phoning and so on and there is no interactions between people in one image. The dataset collected in this paper are concentrating on human interaction between two people aiming to explore this new topic in the research area of action recognition from still images.
Address Mallorca
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 0302-9743 ISBN 978-3-642-31566-4 Medium
Area Expedition Conference AMDO
Notes ISE Approved no
Call Number Admin @ si @ GGT2012 Serial 2030
Permanent link to this record
 
 
Author (up) 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
Volume Issue Pages
Keywords
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.
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 ISE Approved no
Call Number Admin @ si @ GGR2012 Serial 2003
Permanent link to this record
 
 
Author (up) Xavier Boix; Josep M. Gonfaus; Joost Van de Weijer; Andrew Bagdanov; Joan Serrat; Jordi Gonzalez
Title Harmony Potentials: Fusing Global and Local Scale for Semantic Image Segmentation Type Journal Article
Year 2012 Publication International Journal of Computer Vision Abbreviated Journal IJCV
Volume 96 Issue 1 Pages 83-102
Keywords
Abstract The Hierarchical Conditional Random Field(HCRF) model have been successfully applied to a number of image labeling problems, including image segmentation. However, existing HCRF models of image segmentation do not allow multiple classes to be assigned to a single region, which limits their ability to incorporate contextual information across multiple scales.
At higher scales in the image, this representation yields an oversimpli ed model since multiple classes can be reasonably expected to appear within large regions. This simpli ed model particularly limits the impact of information at higher scales. Since class-label information at these scales is usually more reliable than at lower, noisier scales, neglecting this information is undesirable. To
address these issues, we propose a new consistency potential for image labeling problems, which we call the harmony potential. It can encode any possible combi-
nation of labels, penalizing only unlikely combinations of classes. We also propose an e ective sampling strategy over this expanded label set that renders tractable the underlying optimization problem. Our approach obtains state-of-the-art results on two challenging, standard benchmark datasets for semantic image segmentation: PASCAL VOC 2010, and MSRC-21.
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 0920-5691 ISBN Medium
Area Expedition Conference
Notes ISE;CIC;ADAS Approved no
Call Number Admin @ si @ BGW2012 Serial 1718
Permanent link to this record