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Author (up) Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil
Title An illumination model of the trachea appearance in videobronchoscopy images Type Book Chapter
Year 2012 Publication Image Analysis and Recognition Abbreviated Journal LNCS
Volume 7325 Issue Pages 313-320
Keywords Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation
Abstract Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution.
Address Aveiro, Portugal
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
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 978-3-642-31297-7 Medium
Area 800 Expedition Conference ICIAR
Notes MV;IAM Approved no
Call Number IAM @ iam @ SSR2012 Serial 1898
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Author (up) Carolina Malagelada; F.De Lorio; Santiago Segui; S. Mendez; Michal Drozdzal; Jordi Vitria; Petia Radeva; J.Santos; Anna Accarino; Juan R. Malagelada; Fernando Azpiroz
Title Functional gut disorders or disordered gut function? Small bowel dysmotility evidenced by an original technique Type Journal Article
Year 2012 Publication Neurogastroenterology & Motility Abbreviated Journal NEUMOT
Volume 24 Issue 3 Pages 223-230
Keywords capsule endoscopy;computer vision analysis;machine learning technique;small bowel motility
Abstract JCR Impact Factor 2010: 3.349
Background This study aimed to determine the proportion of cases with abnormal intestinal motility among patients with functional bowel disorders. To this end, we applied an original method, previously developed in our laboratory, for analysis of endoluminal images obtained by capsule endoscopy. This novel technology is based on computer vision and machine learning techniques.
 Methods The endoscopic capsule (Pillcam SB1; Given Imaging, Yokneam, Israel) was administered to 80 patients with functional bowel disorders and 70 healthy subjects. Endoluminal image analysis was performed with a computer vision program developed for the evaluation of contractile events (luminal occlusions and radial wrinkles), non-contractile patterns (open tunnel and smooth wall patterns), type of content (secretions, chyme) and motion of wall and contents. Normality range and discrimination of abnormal cases were established by a machine learning technique. Specifically, an iterative classifier (one-class support vector machine) was applied in a random population of 50 healthy subjects as a training set and the remaining subjects (20 healthy subjects and 80 patients) as a test set.
 Key Results The classifier identified as abnormal 29% of patients with functional diseases of the bowel (23 of 80), and as normal 97% of healthy subjects (68 of 70) (P < 0.05 by chi-squared test). Patients identified as abnormal clustered in two groups, which exhibited either a hyper- or a hypodynamic motility pattern. The motor behavior was unrelated to clinical features.
Conclusions &  Inferences With appropriate methodology, abnormal intestinal motility can be demonstrated in a significant proportion of patients with functional bowel disorders, implying a pathologic disturbance of gut physiology.
Address
Corporate Author Thesis
Publisher Wiley Online Library 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; OR; MV Approved no
Call Number Admin @ si @ MLS2012 Serial 1830
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Author (up) Cesar Isaza; Joaquin Salas; Bogdan Raducanu
Title Synthetic ground truth dataset to detect shadow cast by static objects in outdoor Type Conference Article
Year 2012 Publication 1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications Abbreviated Journal
Volume Issue Pages art. 11
Keywords
Abstract In this paper, we propose a precise synthetic ground truth dataset to study the problem of detection of the shadows cast by static objects in outdoor environments during extended periods of time (days). For our dataset, we have created a virtual scenario using a rendering software. To increase the realism of the simulated environment, we have defined the scenario in a precise geographical location. In our dataset the sun is by far the main illumination source. The sun position during the simulation time takes into consideration factors related to the geographical location, such as the latitude, longitude, elevation above sea level, and precise image capturing day and time. In our simulation the camera remains fixed. The dataset consists of seven days of simulation, from 10:00am to 5:00pm. Images are captured every 10 seconds. The shadows' ground truth is automatically computed by the rendering software.
Address Capri, Italy
Corporate Author Thesis
Publisher ACM Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-4503-1405-3 Medium
Area Expedition Conference VIGTA
Notes OR;MV Approved no
Call Number Admin @ si @ ISR2012a Serial 2037
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Author (up) Cesar Isaza; Joaquin Salas; Bogdan Raducanu
Title Evaluation of Intrinsic Image Algorithms to Detect the Shadows Cast by Static Objects Outdoors Type Journal Article
Year 2012 Publication Sensors Abbreviated Journal SENS
Volume 12 Issue 10 Pages 13333-13348
Keywords
Abstract In some automatic scene analysis applications, the presence of shadows becomes a nuisance that is necessary to deal with. As a consequence, a preliminary stage in many computer vision algorithms is to attenuate their effect. In this paper, we focus our attention on the detection of shadows cast by static objects outdoors, as the scene is viewed for extended periods of time (days, weeks) from a fixed camera and considering daylight intervals where the main source of light is the sun. In this context, we report two contributions. First, we introduce the use of synthetic images for which ground truth can be generated automatically, avoiding the tedious effort of manual annotation. Secondly, we report a novel application of the intrinsic image concept to the automatic detection of shadows cast by static objects in outdoors. We make both a quantitative and a qualitative evaluation of several algorithms based on this image representation. For the quantitative evaluation, we used the synthetic data set, while for the qualitative evaluation we used both data sets. Our experimental results show that the evaluated methods can partially solve the problem of shadow detection.
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 OR;MV Approved no
Call Number Admin @ si @ ISR2012b Serial 2173
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Author (up) Cristhian Aguilera; Fernando Barrera; Angel Sappa; Ricardo Toledo
Title A Novel SIFT-Like-Based Approach for FIR-VS Images Registration Type Conference Article
Year 2012 Publication 11th Quantitative InfraRed Thermography Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Naples, 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 ISBN Medium
Area Expedition Conference QIRT
Notes ADAS; TV Approved no
Call Number Admin @ si @ ABS2012 Serial 2017
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Author (up) Cristhian Aguilera; Fernando Barrera; Felipe Lumbreras; Angel Sappa; Ricardo Toledo
Title Multispectral Image Feature Points Type Journal Article
Year 2012 Publication Sensors Abbreviated Journal SENS
Volume 12 Issue 9 Pages 12661-12672
Keywords multispectral image descriptor; color and infrared images; feature point descriptor
Abstract Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.
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 Admin @ si @ ABL2012 Serial 2154
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Author (up) Cristhian Aguilera; M.Ramos; Angel Sappa
Title Simulated Annealing: A Novel Application of Image Processing in the Wood Area Type Book Chapter
Year 2012 Publication Simulated Annealing – Advances, Applications and Hybridizations Abbreviated Journal
Volume Issue Pages 91-104
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor Marcos de Sales Guerra Tsuzuki
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-953-51-0710-1 Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ ARS2012 Serial 2156
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Author (up) David Fernandez; Josep Llados; Alicia Fornes; R.Manmatha
Title On Influence of Line Segmentation in Efficient Word Segmentation in Old Manuscripts Type Conference Article
Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 763-768
Keywords document image processing;handwritten character recognition;history;image segmentation;Spanish document;historical document;line segmentation;old handwritten document;old manuscript;word segmentation;Bifurcation;Dynamic programming;Handwriting recognition;Image segmentation;Measurement;Noise;Skeleton;Segmentation;document analysis;document and text processing;handwriting analysis;heuristics;path-finding
Abstract he objective of this work is to show the importance of a good line segmentation to obtain better results in the segmentation of words of historical documents. We have used the approach developed by Manmatha and Rothfeder [1] to segment words in old handwritten documents. In their work the lines of the documents are extracted using projections. In this work, we have developed an approach to segment lines more efficiently. The new line segmentation algorithm tackles with skewed, touching and noisy lines, so it is significantly improves word segmentation. Experiments using Spanish documents from the Marriages Database of the Barcelona Cathedral show that this approach reduces the error rate by more than 20%
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 978-1-4673-2262-1 Medium
Area Expedition Conference ICFHR
Notes DAG Approved no
Call Number Admin @ si @ FLF2012 Serial 2200
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Author (up) David Geronimo; Frederic Lerasle; Antonio Lopez
Title State-driven particle filter for multi-person tracking Type Conference Article
Year 2012 Publication 11th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal
Volume 7517 Issue Pages 467-478
Keywords human tracking
Abstract Multi-person tracking can be exploited in applications such as driver assistance, surveillance, multimedia and human-robot interaction. With the help of human detectors, particle filters offer a robust method able to filter noisy detections and provide temporal coherence. However, some traditional problems such as occlusions with other targets or the scene, temporal drifting or even the lost targets detection are rarely considered, making the systems performance decrease. Some authors propose to overcome these problems using heuristics not explained
and formalized in the papers, for instance by defining exceptions to the model updating depending on tracks overlapping. In this paper we propose to formalize these events by the use of a state-graph, defining the current state of the track (e.g., potential , tracked, occluded or lost) and the transitions between states in an explicit way. This approach has the advantage of linking track actions such as the online underlying models updating, which gives flexibility to the system. It provides an explicit representation to adapt the multiple parallel trackers depending on the context, i.e., each track can make use of a specific filtering strategy, dynamic model, number of particles, etc. depending on its state. We implement this technique in a single-camera multi-person tracker and test
it in public video sequences.
Address Brno, Chzech Republic
Corporate Author Thesis
Publisher Springer Place of Publication Heidelberg Editor J. Blanc-Talon et al.
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ACIVS
Notes ADAS Approved yes
Call Number GLL2012; ADAS @ adas @ gll2012a Serial 1990
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Author (up) David Masip; Alexander Todorov; Jordi Vitria
Title The Role of Facial Regions in Evaluating Social Dime Type Conference Article
Year 2012 Publication 12th European Conference on Computer Vision – Workshops and Demonstrations Abbreviated Journal
Volume 7584 Issue II Pages 210-219
Keywords Workshops and Demonstrations
Abstract Facial trait judgments are an important information cue for people. Recent works in the Psychology field have stated the basis of face evaluation, defining a set of traits that we evaluate from faces (e.g. dominance, trustworthiness, aggressiveness, attractiveness, threatening or intelligence among others). We rapidly infer information from others faces, usually after a short period of time (< 1000ms) we perceive a certain degree of dominance or trustworthiness of another person from the face. Although these perceptions are not necessarily accurate, they influence many important social outcomes (such as the results of the elections or the court decisions). This topic has also attracted the attention of Computer Vision scientists, and recently a computational model to automatically predict trait evaluations from faces has been proposed. These systems try to mimic the human perception by means of applying machine learning classifiers to a set of labeled data. In this paper we perform an experimental study on the specific facial features that trigger the social inferences. Using previous results from the literature, we propose to use simple similarity maps to evaluate which regions of the face influence the most the trait inferences. The correlation analysis is performed using only appearance, and the results from the experiments suggest that each trait is correlated with specific facial characteristics.
Address Florence, Italy
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor Andrea Fusiello, Vittorio Murino, Rita Cucchiara
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-33867-0 Medium
Area Expedition Conference ECCVW
Notes OR;MV Approved no
Call Number Admin @ si @ MTV2012 Serial 2171
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Author (up) David Roche; Debora Gil; Jesus Giraldo
Title Assessing agonist efficacy in an uncertain Em world Type Conference Article
Year 2012 Publication 40th Keystone Symposia on mollecular and celular biology Abbreviated Journal
Volume Issue Pages 79
Keywords
Abstract The operational model of agonism has been widely used for the analysis of agonist action since its formulation in 1983. The model includes the Em parameter, which is defined as the maximum response of the system. The methods for Em estimation provide Em values not significantly higher than the maximum responses achieved by full agonists. However, it has been found that that some classes of compounds as, for instance, superagonists and positive allosteric modulators can increase the full agonist maximum response, implying upper limits for Em and thereby posing doubts on the validity of Em estimates. Because of the correlation between Em and operational efficacy, τ, wrong Em estimates will yield wrong τ estimates.
In this presentation, the operational model of agonism and various methods for the simulation of allosteric modulation will be analyzed. Alternatives for curve fitting will be presented and discussed.
Address Fairmont Banff Springs, Banff, Alberta, Canada
Corporate Author Keystone Symposia Thesis
Publisher Keystone Symposia Place of Publication Editor A. Christopoulus and M. Bouvier
Language english Summary Language english Original Title
Series Editor Keystone Symposia Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference KSMCB
Notes IAM Approved no
Call Number IAM @ iam @ RGG2012 Serial 1855
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Author (up) David Vazquez; Antonio Lopez; Daniel Ponsa
Title Unsupervised Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection Type Conference Article
Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 3492 - 3495
Keywords Pedestrian Detection; Domain Adaptation; Virtual worlds
Abstract Vision-based object detectors are crucial for different applications. They rely on learnt object models. Ideally, we would like to deploy our vision system in the scenario where it must operate, and lead it to self-learn how to distinguish the objects of interest, i.e., without human intervention. However, the learning of each object model requires labelled samples collected through a tiresome manual process. For instance, we are interested in exploring the self-training of a pedestrian detector for driver assistance systems. Our first approach to avoid manual labelling consisted in the use of samples coming from realistic computer graphics, so that their labels are automatically available [12]. This would make possible the desired self-training of our pedestrian detector. However, as we showed in [14], between virtual and real worlds it may be a dataset shift. In order to overcome it, we propose the use of unsupervised domain adaptation techniques that avoid human intervention during the adaptation process. In particular, this paper explores the use of the transductive SVM (T-SVM) learning algorithm in order to adapt virtual and real worlds for pedestrian detection (Fig. 1).
Address Tsukuba Science City, Japan
Corporate Author Thesis
Publisher IEEE Place of Publication Tsukuba Science City, JAPAN 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 ADAS Approved no
Call Number ADAS @ adas @ VLP2012 Serial 1981
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Author (up) Debora Gil;Agnes Borras;Ruth Aris;Mariano Vazquez;Pierre Lafortune; Guillame Houzeaux
Title What a difference in biomechanics cardiac fiber makes Type Conference Article
Year 2012 Publication Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges Abbreviated Journal
Volume 7746 Issue Pages 253-260
Keywords
Abstract Computational simulations of the heart are a powerful tool for a comprehensive understanding of cardiac function and its intrinsic relationship with its muscular architecture. Cardiac biomechanical models require a vector field representing the orientation of cardiac fibers. A wrong orientation of the fibers can lead to a
non-realistic simulation of the heart functionality. In this paper we explore the impact of the fiber information on the simulated biomechanics of cardiac muscular anatomy. We have used the John Hopkins database to perform a biomechanical simulation using both a synthetic benchmark fiber distribution and the data obtained experimentally from DTI. Results illustrate how differences in fiber orientation affect heart deformation along cardiac cycle.
Address Nice, France
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 978-3-642-36960-5 Medium
Area Expedition Conference STACOM
Notes IAM Approved no
Call Number IAM @ iam @ GBA2012 Serial 1987
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Author (up) Diego Alejandro Cheda
Title Monocular Depth Cues in Computer Vision Applications Type Book Whole
Year 2012 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Depth perception is a key aspect of human vision. It is a routine and essential visual task that the human do effortlessly in many daily activities. This has often been associated with stereo vision, but humans have an amazing ability to perceive depth relations even from a single image by using several monocular cues.

In the computer vision field, if image depth information were available, many tasks could be posed from a different perspective for the sake of higher performance and robustness. Nevertheless, given a single image, this possibility is usually discarded, since obtaining depth information has frequently been performed by three-dimensional reconstruction techniques, requiring two or more images of the same scene taken from different viewpoints. Recently, some proposals have shown the feasibility of computing depth information from single images. In essence, the idea is to take advantage of a priori knowledge of the acquisition conditions and the observed scene to estimate depth from monocular pictorial cues. These approaches try to precisely estimate the scene depth maps by employing computationally demanding techniques. However, to assist many computer vision algorithms, it is not really necessary computing a costly and detailed depth map of the image. Indeed, just a rough depth description can be very valuable in many problems.

In this thesis, we have demonstrated how coarse depth information can be integrated in different tasks following alternative strategies to obtain more precise and robust results. In that sense, we have proposed a simple, but reliable enough technique, whereby image scene regions are categorized into discrete depth ranges to build a coarse depth map. Based on this representation, we have explored the potential usefulness of our method in three application domains from novel viewpoints: camera rotation parameters estimation, background estimation and pedestrian candidate generation. In the first case, we have computed camera rotation mounted in a moving vehicle applying two novels methods based on distant elements in the image, where the translation component of the image flow vectors is negligible. In background estimation, we have proposed a novel method to reconstruct the background by penalizing close regions in a cost function, which integrates color, motion, and depth terms. Finally, we have benefited of geometric and depth information available on single images for pedestrian candidate generation to significantly reduce the number of generated windows to be further processed by a pedestrian classifier. In all cases, results have shown that our approaches contribute to better performances.
Address
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Daniel Ponsa;Antonio Lopez
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 Admin @ si @ Che2012 Serial 2210
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Author (up) Diego Cheda; Daniel Ponsa; Antonio Lopez
Title Monocular Egomotion Estimation based on Image Matching Type Conference Article
Year 2012 Publication 1st International Conference on Pattern Recognition Applications and Methods Abbreviated Journal
Volume Issue Pages 425-430
Keywords SLAM
Abstract
Address Portugal
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 ICPRAM
Notes ADAS Approved no
Call Number Admin @ si @ CPL2012a;; ADAS @ adas @ Serial 2011
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