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Author Xavier Baro; David Masip; Elena Planas; Julia Minguillon
Title PeLP: Plataforma para el Aprendizaje de Lenguajes de Programación Type Miscellaneous
Year 2013 Publication XV Jornadas de Enseñanza Universitaria de la Informatica Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference JENUI
Notes OR;HuPBA;MV Approved no
Call Number Admin @ si @ BMP2013 Serial 2237
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Author Victor Borjas; Jordi Vitria; Petia Radeva
Title Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments Type Conference Article
Year 2013 Publication 13th IAPR Conference on Machine Vision Applications Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Best Poster AwardOne of the big challenges of today person detectors is the decreasing of the false positive rate. In this paper, we propose a novel framework to customize person detectors in static camera scenarios in order to reduce this rate. This scheme includes background modeling for subtraction based on gradient histograms and Mean-Shift clustering. Our experiments show that the detection improved compared to using only the output from the pedestrian detector reducing 87% of the false positives and therefore the overall precision of the detection
was increased signi cantly.
Address Kyoto; Japan; May 2013
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MVA
Notes OR; MILAB;MV Approved no
Call Number BVR2013 Serial 2238
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Author Fadi Dornaika; Bogdan Raducanu
Title Out-of-Sample Embedding for Manifold Learning Applied to Face Recognition Type Conference Article
Year 2013 Publication IEEE International Workshop on Analysis and Modeling of Faces and Gestures Abbreviated Journal
Volume Issue Pages 862-868
Keywords
Abstract Manifold learning techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data---the out-of-sample problem. For the first aspect, the proposed schemes were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only reached for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that sparse coding theory not only serves for automatic graph reconstruction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the k-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on four public face databases. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes.
Address Portland; USA; June 2013
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CVPRW
Notes OR; 600.046;MV Approved no
Call Number Admin @ si @ DoR2013 Serial 2236
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Author Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria
Title An Application for Efficient Error-Free Labeling of Medical Images Type Book Chapter
Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal
Volume 48 Issue Pages 1-16
Keywords
Abstract In this chapter we describe an application for efficient error-free labeling of medical images. In this scenario, the compilation of a complete training set for building a realistic model of a given class of samples is not an easy task, making the process tedious and time consuming. For this reason, there is a need for interactive labeling applications that minimize the effort of the user while providing error-free labeling. We propose a new algorithm that is based on data similarity in feature space. This method actively explores data in order to find the best label-aligned clustering and exploits it to reduce the labeler effort, that is measured by the number of “clicks. Moreover, error-free labeling is guaranteed by the fact that all data and their labels proposals are visually revised by en expert.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium
Area Expedition Conference
Notes MILAB; OR;MV Approved no
Call Number Admin @ si @ DSR2013 Serial 2235
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Author Marina Alberti; Simone Balocco; Xavier Carrillo; Josefina Mauri; Petia Radeva
Title Automatic non-rigid temporal alignment of IVUS sequences: method and quantitative validation Type Journal Article
Year 2013 Publication Ultrasound in Medicine and Biology Abbreviated Journal UMB
Volume 39 Issue 9 Pages 1698-712
Keywords Intravascular ultrasound; Dynamic time warping; Non-rigid alignment; Sequence matching; Partial overlapping strategy
Abstract Clinical studies on atherosclerosis regression/progression performed by intravascular ultrasound analysis would benefit from accurate alignment of sequences of the same patient before and after clinical interventions and at follow-up. In this article, a methodology for automatic alignment of intravascular ultrasound sequences based on the dynamic time warping technique is proposed. The non-rigid alignment is adapted to the specific task by applying it to multidimensional signals describing the morphologic content of the vessel. Moreover, dynamic time warping is embedded into a framework comprising a strategy to address partial overlapping between acquisitions and a term that regularizes non-physiologic temporal compression/expansion of the sequences. Extensive validation is performed on both synthetic and in vivo data. The proposed method reaches alignment errors of approximately 0.43 mm for pairs of sequences acquired during the same intervention phase and 0.77 mm for pairs of sequences acquired at successive intervention stages.
Address
Corporate Author Thesis
Publisher Place of Publication Editor (down)
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 @ ABC2013 Serial 2313
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Author Simone Balocco; Carlo Gatta; Francesco Ciompi; A. Wahle; Petia Radeva; S. Carlier; G. Unal; E. Sanidas; F. Mauri; X. Carillo; T. Kovarnik; C. Wang; H. Chen; T. P. Exarchos; D. I. Fotiadis; F. Destrempes; G. Cloutier; Oriol Pujol; Marina Alberti; E. G. Mendizabal-Ruiz; M. Rivera; T. Aksoy; R. W. Downe; I. A. Kakadiaris
Title Standardized evaluation methodology and reference database for evaluating IVUS image segmentation Type Journal Article
Year 2014 Publication Computerized Medical Imaging and Graphics Abbreviated Journal CMIG
Volume 38 Issue 2 Pages 70-90
Keywords IVUS (intravascular ultrasound); Evaluation framework; Algorithm comparison; Image segmentation
Abstract This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated.
We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have
been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be
solved.
Address
Corporate Author Thesis
Publisher Place of Publication Editor (down)
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; LAMP; HuPBA; 600.046; 600.063; 600.079 Approved no
Call Number Admin @ si @ BGC2013 Serial 2314
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Author Santiago Segui; Michal Drozdzal; Fernando Vilariño; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitria
Title Categorization and Segmentation of Intestinal Content Frames for Wireless Capsule Endoscopy Type Journal Article
Year 2012 Publication IEEE Transactions on Information Technology in Biomedicine Abbreviated Journal TITB
Volume 16 Issue 6 Pages 1341-1352
Keywords
Abstract Wireless capsule endoscopy (WCE) is a device that allows the direct visualization of gastrointestinal tract with minimal discomfort for the patient, but at the price of a large amount of time for screening. In order to reduce this time, several works have proposed to automatically remove all the frames showing intestinal content. These methods label frames as {intestinal content – clear} without discriminating between types of content (with different physiological meaning) or the portion of image covered. In addition, since the presence of intestinal content has been identified as an indicator of intestinal motility, its accurate quantification can show a potential clinical relevance. In this paper, we present a method for the robust detection and segmentation of intestinal content in WCE images, together with its further discrimination between turbid liquid and bubbles. Our proposal is based on a twofold system. First, frames presenting intestinal content are detected by a support vector machine classifier using color and textural information. Second, intestinal content frames are segmented into {turbid, bubbles, and clear} regions. We show a detailed validation using a large dataset. Our system outperforms previous methods and, for the first time, discriminates between turbid from bubbles media.
Address
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1089-7771 ISBN Medium
Area 800 Expedition Conference
Notes MILAB; MV; OR;SIAI Approved no
Call Number Admin @ si @ SDV2012 Serial 2124
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Author Bogdan Raducanu; Fadi Dornaika
Title Texture-independent recognition of facial expressions in image snapshots and videos Type Journal Article
Year 2013 Publication Machine Vision and Applications Abbreviated Journal MVA
Volume 24 Issue 4 Pages 811-820
Keywords
Abstract This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines.
Address
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0932-8092 ISBN Medium
Area Expedition Conference
Notes OR; 600.046; 605.203;MV Approved no
Call Number Admin @ si @ RaD2013 Serial 2230
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Author Ferran Diego; Joan Serrat; Antonio Lopez
Title Joint spatio-temporal alignment of sequences Type Journal Article
Year 2013 Publication IEEE Transactions on Multimedia Abbreviated Journal TMM
Volume 15 Issue 6 Pages 1377-1387
Keywords video alignment
Abstract Video alignment is important in different areas of computer vision such as wide baseline matching, action recognition, change detection, video copy detection and frame dropping prevention. Current video alignment methods usually deal with a relatively simple case of fixed or rigidly attached cameras or simultaneous acquisition. Therefore, in this paper we propose a joint video alignment for bringing two video sequences into a spatio-temporal alignment. Specifically, the novelty of the paper is to formulate the video alignment to fold the spatial and temporal alignment into a single alignment framework. This simultaneously satisfies a frame-correspondence and frame-alignment similarity; exploiting the knowledge among neighbor frames by a standard pairwise Markov random field (MRF). This new formulation is able to handle the alignment of sequences recorded at different times by independent moving cameras that follows a similar trajectory, and also generalizes the particular cases that of fixed geometric transformation and/or linear temporal mapping. We conduct experiments on different scenarios such as sequences recorded simultaneously or by moving cameras to validate the robustness of the proposed approach. The proposed method provides the highest video alignment accuracy compared to the state-of-the-art methods on sequences recorded from vehicles driving along the same track at different times.
Address
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1520-9210 ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ DSL2013; ADAS @ adas @ Serial 2228
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Author Cesar Isaza; Joaquin Salas; Bogdan Raducanu
Title Rendering ground truth data sets to detect shadows cast by static objects in outdoors Type Journal Article
Year 2014 Publication Multimedia Tools and Applications Abbreviated Journal MTAP
Volume 70 Issue 1 Pages 557-571
Keywords Synthetic ground truth data set; Sun position; Shadow detection; Static objects shadow detection
Abstract In our work, we are particularly interested in studying the shadows cast by static objects in outdoor environments, during daytime. To assess the accuracy of a shadow detection algorithm, we need ground truth information. The collection of such information is a very tedious task because it is a process that requires manual annotation. To overcome this severe limitation, we propose in this paper a methodology to automatically render ground truth using a virtual environment. To increase the degree of realism and usefulness of the simulated environment, we incorporate in the scenario the precise longitude, latitude and elevation of the actual location of the object, as well as the sun’s position for a given time and day. To evaluate our method, we consider a qualitative and a quantitative comparison. In the quantitative one, we analyze the shadow cast by a real object in a particular geographical location and its corresponding rendered model. To evaluate qualitatively the methodology, we use some ground truth images obtained both manually and automatically.
Address
Corporate Author Thesis
Publisher Springer US Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1380-7501 ISBN Medium
Area Expedition Conference
Notes OR;MV Approved no
Call Number Admin @ si @ ISR2014 Serial 2229
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Author German Ros; J. Guerrero; Angel Sappa; Antonio Lopez
Title VSLAM pose initialization via Lie groups and Lie algebras optimization Type Conference Article
Year 2013 Publication Proceedings of IEEE International Conference on Robotics and Automation Abbreviated Journal
Volume Issue Pages 5740 - 5747
Keywords SLAM
Abstract We present a novel technique for estimating initial 3D poses in the context of localization and Visual SLAM problems. The presented approach can deal with noise, outliers and a large amount of input data and still performs in real time in a standard CPU. Our method produces solutions with an accuracy comparable to those produced by RANSAC but can be much faster when the percentage of outliers is high or for large amounts of input data. On the current work we propose to formulate the pose estimation as an optimization problem on Lie groups, considering their manifold structure as well as their associated Lie algebras. This allows us to perform a fast and simple optimization at the same time that conserve all the constraints imposed by the Lie group SE(3). Additionally, we present several key design concepts related with the cost function and its Jacobian; aspects that are critical for the good performance of the algorithm.
Address Karlsruhe; Germany; May 2013
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1050-4729 ISBN 978-1-4673-5641-1 Medium
Area Expedition Conference ICRA
Notes ADAS; 600.054; 600.055; 600.057 Approved no
Call Number Admin @ si @ RGS2013a; ADAS @ adas @ Serial 2225
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Author David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados
Title Integrating Visual and Textual Cues for Query-by-String Word Spotting Type Conference Article
Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 511 - 515
Keywords
Abstract In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances.
Address Washington; USA; August 2013
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1520-5363 ISBN Medium
Area Expedition Conference ICDAR
Notes DAG; ADAS; 600.045; 600.055; 600.061 Approved no
Call Number Admin @ si @ ART2013 Serial 2224
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Author Ariel Amato; Ivan Huerta; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez
Title Moving Cast Shadows Detection Methods for Video Surveillance Applications Type Book Chapter
Year 2014 Publication Augmented Vision and Reality Abbreviated Journal
Volume 6 Issue Pages 23-47
Keywords
Abstract Moving cast shadows are a major concern in today’s performance from broad range of many vision-based surveillance applications because they highly difficult the object classification task. Several shadow detection methods have been reported in the literature during the last years. They are mainly divided into two domains. One usually works with static images, whereas the second one uses image sequences, namely video content. In spite of the fact that both cases can be analogously analyzed, there is a difference in the application field. The first case, shadow detection methods can be exploited in order to obtain additional geometric and semantic cues about shape and position of its casting object (‘shape from shadows’) as well as the localization of the light source. While in the second one, the main purpose is usually change detection, scene matching or surveillance (usually in a background subtraction context). Shadows can in fact modify in a negative way the shape and color of the target object and therefore affect the performance of scene analysis and interpretation in many applications. This chapter wills mainly reviews shadow detection methods as well as their taxonomies related with the second case, thus aiming at those shadows which are associated with moving objects (moving shadows).
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2190-5916 ISBN 978-3-642-37840-9 Medium
Area Expedition Conference
Notes ISE; 605.203; 600.049; 302.018; 302.012; 600.078 Approved no
Call Number Admin @ si @ AHM2014 Serial 2223
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Author Marc Castello; Jordi Gonzalez; Ariel Amato; Pau Baiget; Carles Fernandez; Josep M. Gonfaus; Ramon Mollineda; Marco Pedersoli; Nicolas Perez de la Blanca; Xavier Roca
Title Exploiting Multimodal Interaction Techniques for Video-Surveillance Type Book Chapter
Year 2013 Publication Multimodal Interaction in Image and Video Applications Intelligent Systems Reference Library Abbreviated Journal
Volume 48 Issue 8 Pages 135-151
Keywords
Abstract In this paper we present an example of a video surveillance application that exploits Multimodal Interactive (MI) technologies. The main objective of the so-called VID-Hum prototype was to develop a cognitive artificial system for both the detection and description of a particular set of human behaviours arising from real-world events. The main procedure of the prototype described in this chapter entails: (i) adaptation, since the system adapts itself to the most common behaviours (qualitative data) inferred from tracking (quantitative data) thus being able to recognize abnormal behaviors; (ii) feedback, since an advanced interface based on Natural Language understanding allows end-users the communicationwith the prototype by means of conceptual sentences; and (iii) multimodality, since a virtual avatar has been designed to describe what is happening in the scene, based on those textual interpretations generated by the prototype. Thus, the MI methodology has provided an adequate framework for all these cooperating processes.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor (down)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium
Area Expedition Conference
Notes ISE; 605.203; 600.049 Approved no
Call Number CGA2013 Serial 2222
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Author Francisco Javier Orozco; Ognjen Rudovic; Jordi Gonzalez; Maja Pantic
Title Hierarchical On-line Appearance-Based Tracking for 3D Head Pose, Eyebrows, Lips, Eyelids and Irises Type Journal Article
Year 2013 Publication Image and Vision Computing Abbreviated Journal IMAVIS
Volume 31 Issue 4 Pages 322-340
Keywords On-line appearance models; Levenberg–Marquardt algorithm; Line-search optimization; 3D face tracking; Facial action tracking; Eyelid tracking; Iris tracking
Abstract In this paper, we propose an On-line Appearance-Based Tracker (OABT) for simultaneous tracking of 3D head pose, lips, eyebrows, eyelids and irises in monocular video sequences. In contrast to previously proposed tracking approaches, which deal with face and gaze tracking separately, our OABT can also be used for eyelid and iris tracking, as well as 3D head pose, lips and eyebrows facial actions tracking. Furthermore, our approach applies an on-line learning of changes in the appearance of the tracked target. Hence, the prior training of appearance models, which usually requires a large amount of labeled facial images, is avoided. Moreover, the proposed method is built upon a hierarchical combination of three OABTs, which are optimized using a Levenberg–Marquardt Algorithm (LMA) enhanced with line-search procedures. This, in turn, makes the proposed method robust to changes in lighting conditions, occlusions and translucent textures, as evidenced by our experiments. Finally, the proposed method achieves head and facial actions tracking in real-time.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor (down)
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; 605.203; 302.012; 302.018; 600.049 Approved no
Call Number ORG2013 Serial 2221
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