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Author Marc Bolaños; Maite Garolera; Petia Radeva
Title Active labeling application applied to food-related object recognition Type Conference Article
Year 2013 Publication 5th International Workshop on Multimedia for Cooking & Eating Activities Abbreviated Journal
Volume Issue Pages 45-50
Keywords
Abstract Every day, lifelogging devices, available for recording different aspects of our daily life, increase in number, quality and functions, just like the multiple applications that we give to them. Applying wearable devices to analyse the nutritional habits of people is a challenging application based on acquiring and analyzing life records in long periods of time. However, to extract the information of interest related to the eating patterns of people, we need automatic methods to process large amount of life-logging data (e.g. recognition of food-related objects). Creating a rich set of manually labeled samples to train the algorithms is slow, tedious and subjective. To address this problem, we propose a novel method in the framework of Active Labeling for construct- ing a training set of thousands of images. Inspired by the hierarchical sampling method for active learning [6], we propose an Active forest that organizes hierarchically the data for easy and fast labeling. Moreover, introducing a classifier into the hierarchical structures, as well as transforming the feature space for better data clustering, additionally im- prove the algorithm. Our method is successfully tested to label 89.700 food-related objects and achieves significant reduction in expert time labelling.

Active labeling application applied to food-related object recognition ResearchGate. Available from: http://www.researchgate.net/publication/262252017Activelabelingapplicationappliedtofood-relatedobjectrecognition [accessed Jul 14, 2015].
Address Barcelona; October 2013
Corporate Author Thesis
Publisher Place of Publication Editor
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Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) ISBN Medium
Area Expedition Conference ACM-CEA
Notes MILAB Approved no
Call Number Admin @ si @ BGR2013b Serial 2637
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Author Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados
Title Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans Type Conference Article
Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Bethlehem; PA; USA; August 2013
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 (up) ISBN Medium
Area Expedition Conference GREC
Notes DAG; 600.045; 600.061; 600.056 Approved no
Call Number Admin @ si @ HFF2013b Serial 2695
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Author Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez
Title Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies Type Conference Article
Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Bethlehem; PA; USA; August 2013
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 (up) ISBN Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number Admin @ si @ HVS2013b Serial 2696
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Author A.S. Coquel; Jean-Pascal Jacob; M. Primet; A. Demarez; Mariella Dimiccoli; T. Julou; L. Moisan; A. Lindner; H. Berry
Title Localization of protein aggregation in Escherichia coli is governed by diffusion and nucleoid macromolecular crowding effect Type Journal Article
Year 2013 Publication Plos Computational Biology Abbreviated Journal PCB
Volume 9 Issue 4 Pages
Keywords
Abstract Aggregates of misfolded proteins are a hallmark of many age-related diseases. Recently, they have been linked to aging of Escherichia coli (E. coli) where protein aggregates accumulate at the old pole region of the aging bacterium. Because of the potential of E. coli as a model organism, elucidating aging and protein aggregation in this bacterium may pave the way to significant advances in our global understanding of aging. A first obstacle along this path is to decipher the mechanisms by which protein aggregates are targeted to specific intercellular locations. Here, using an integrated approach based on individual-based modeling, time-lapse fluorescence microscopy and automated image analysis, we show that the movement of aging-related protein aggregates in E. coli is purely diffusive (Brownian). Using single-particle tracking of protein aggregates in live E. coli cells, we estimated the average size and diffusion constant of the aggregates. Our results provide evidence that the aggregates passively diffuse within the cell, with diffusion constants that depend on their size in agreement with the Stokes-Einstein law. However, the aggregate displacements along the cell long axis are confined to a region that roughly corresponds to the nucleoid-free space in the cell pole, thus confirming the importance of increased macromolecular crowding in the nucleoids. We thus used 3D individual-based modeling to show that these three ingredients (diffusion, aggregation and diffusion hindrance in the nucleoids) are sufficient and necessary to reproduce the available experimental data on aggregate localization in the cells. Taken together, our results strongly support the hypothesis that the localization of aging-related protein aggregates in the poles of E. coli results from the coupling of passive diffusion-aggregation with spatially non-homogeneous macromolecular crowding. They further support the importance of “soft” intracellular structuring (based on macromolecular crowding) in diffusion-based protein localization in E. coli.
Address
Corporate Author Thesis
Publisher Place of Publication Editor : Stanislav Shvartsman, Princeton University, United States of America
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number Admin @ si @CJP2013 Serial 2786
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Author Jose Manuel Alvarez; Theo Gevers; Antonio Lopez
Title Evaluating Color Representation for Online Road Detection Type Conference Article
Year 2013 Publication ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars Abbreviated Journal
Volume Issue Pages 594-595
Keywords
Abstract Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired
using an on-board camera in different real-driving situations.
Address
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Publisher Place of Publication Editor
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Series Editor Series Title Abbreviated Series Title
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ISSN (up) ISBN Medium
Area Expedition Conference CVVT:E2M
Notes ADAS;ISE Approved no
Call Number Admin @ si @ AGL2013 Serial 2794
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Author Jaume Amores
Title Multiple Instance Classification: review, taxonomy and comparative study Type Journal Article
Year 2013 Publication Artificial Intelligence Abbreviated Journal AI
Volume 201 Issue Pages 81-105
Keywords Multi-instance learning; Codebook; Bag-of-Words
Abstract Multiple Instance Learning (MIL) has become an important topic in the pattern recognition community, and many solutions to this problemhave been proposed until now. Despite this fact, there is a lack of comparative studies that shed light into the characteristics and behavior of the different methods. In this work we provide such an analysis focused on the classification task (i.e.,leaving out other learning tasks such as regression). In order to perform our study, we implemented
fourteen methods grouped into three different families. We analyze the performance of the approaches across a variety of well-known databases, and we also study their behavior in synthetic scenarios in order to highlight their characteristics. As a result of this analysis, we conclude that methods that extract global bag-level information show a clearly superior performance in general. In this sense, the analysis permits us to understand why some types of methods are more successful than others, and it permits us to establish guidelines in the design of new MIL
methods.
Address
Corporate Author Thesis
Publisher Elsevier Science Publishers Ltd. Essex, UK Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0004-3702 ISBN Medium
Area Expedition Conference
Notes ADAS; 601.042; 600.057 Approved no
Call Number Admin @ si @ Amo2013 Serial 2273
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Author David Geronimo; Joan Serrat; Antonio Lopez; Ramon Baldrich
Title Traffic sign recognition for computer vision project-based learning Type Journal Article
Year 2013 Publication IEEE Transactions on Education Abbreviated Journal T-EDUC
Volume 56 Issue 3 Pages 364-371
Keywords traffic signs
Abstract This paper presents a graduate course project on computer vision. The aim of the project is to detect and recognize traffic signs in video sequences recorded by an on-board vehicle camera. This is a demanding problem, given that traffic sign recognition is one of the most challenging problems for driving assistance systems. Equally, it is motivating for the students given that it is a real-life problem. Furthermore, it gives them the opportunity to appreciate the difficulty of real-world vision problems and to assess the extent to which this problem can be solved by modern computer vision and pattern classification techniques taught in the classroom. The learning objectives of the course are introduced, as are the constraints imposed on its design, such as the diversity of students' background and the amount of time they and their instructors dedicate to the course. The paper also describes the course contents, schedule, and how the project-based learning approach is applied. The outcomes of the course are discussed, including both the students' marks and their personal feedback.
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Publisher Place of Publication Editor
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Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0018-9359 ISBN Medium
Area Expedition Conference
Notes ADAS; CIC Approved no
Call Number Admin @ si @ GSL2013; ADAS @ adas @ Serial 2160
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Author Albert Gordo; Florent Perronnin; Ernest Valveny
Title Large-scale document image retrieval and classification with runlength histograms and binary embeddings Type Journal Article
Year 2013 Publication Pattern Recognition Abbreviated Journal PR
Volume 46 Issue 7 Pages 1898-1905
Keywords visual document descriptor; compression; large-scale; retrieval; classification
Abstract We present a new document image descriptor based on multi-scale runlength
histograms. This descriptor does not rely on layout analysis and can be
computed efficiently. We show how this descriptor can achieve state-of-theart
results on two very different public datasets in classification and retrieval
tasks. Moreover, we show how we can compress and binarize these descriptors
to make them suitable for large-scale applications. We can achieve state-ofthe-
art results in classification using binary descriptors of as few as 16 to 64
bits.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0031-3203 ISBN Medium
Area Expedition Conference
Notes DAG; 600.042; 600.045; 605.203 Approved no
Call Number Admin @ si @ GPV2013 Serial 2306
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Author Albert Gordo; Alicia Fornes; Ernest Valveny
Title Writer identification in handwritten musical scores with bags of notes Type Journal Article
Year 2013 Publication Pattern Recognition Abbreviated Journal PR
Volume 46 Issue 5 Pages 1337-1345
Keywords
Abstract Writer Identification is an important task for the automatic processing of documents. However, the identification of the writer in graphical documents is still challenging. In this work, we adapt the Bag of Visual Words framework to the task of writer identification in handwritten musical scores. A vanilla implementation of this method already performs comparably to the state-of-the-art. Furthermore, we analyze the effect of two improvements of the representation: a Bhattacharyya embedding, which improves the results at virtually no extra cost, and a Fisher Vector representation that very significantly improves the results at the cost of a more complex and costly representation. Experimental evaluation shows results more than 20 points above the state-of-the-art in a new, challenging dataset.
Address
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0031-3203 ISBN Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ GFV2013 Serial 2307
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Author Veronica Romero; Alicia Fornes; Nicolas Serrano; Joan Andreu Sanchez; A.H. Toselli; Volkmar Frinken; E. Vidal; Josep Llados
Title The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition Type Journal Article
Year 2013 Publication Pattern Recognition Abbreviated Journal PR
Volume 46 Issue 6 Pages 1658-1669
Keywords
Abstract Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demography studies and genealogical research. Automatic processing of historical documents, however, has mostly been focused on single works of literature and less on social records, which tend to have a distinct layout, structure, and vocabulary. Such information is usually collected by expert demographers that devote a lot of time to manually transcribe them. This paper presents a new database, compiled from a marriage license books collection, to support research in automatic handwriting recognition for historical documents containing social records. Marriage license books are documents that were used for centuries by ecclesiastical institutions to register marriage licenses. Books from this collection are handwritten and span nearly half a millennium until the beginning of the 20th century. In addition, a study is presented about the capability of state-of-the-art handwritten text recognition systems, when applied to the presented database. Baseline results are reported for reference in future studies.
Address
Corporate Author Thesis
Publisher Elsevier Science Inc. New York, NY, USA Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0031-3203 ISBN Medium
Area Expedition Conference
Notes DAG; 600.045; 602.006; 605.203 Approved no
Call Number Admin @ si @ RFS2013 Serial 2298
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Author Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
Title A Genetic-based Subspace Analysis Method for Improving Error-Correcting Output Coding Type Journal Article
Year 2013 Publication Pattern Recognition Abbreviated Journal PR
Volume 46 Issue 10 Pages 2830-2839
Keywords Error Correcting Output Codes; Evolutionary computation; Multiclass classification; Feature subspace; Ensemble classification
Abstract Two key factors affecting the performance of Error Correcting Output Codes (ECOC) in multiclass classification problems are the independence of binary classifiers and the problem-dependent coding design. In this paper, we propose an evolutionary algorithm-based approach to the design of an application-dependent codematrix in the ECOC framework. The central idea of this work is to design a three-dimensional codematrix, where the third dimension is the feature space of the problem domain. In order to do that, we consider the feature space in the design process of the codematrix with the aim of improving the independence and accuracy of binary classifiers. The proposed method takes advantage of some basic concepts of ensemble classification, such as diversity of classifiers, and also benefits from the evolutionary approach for optimizing the three-dimensional codematrix, taking into account the problem domain. We provide a set of experimental results using a set of benchmark datasets from the UCI Machine Learning Repository, as well as two real multiclass Computer Vision problems. Both sets of experiments are conducted using two different base learners: Neural Networks and Decision Trees. The results show that the proposed method increases the classification accuracy in comparison with the state-of-the-art ECOC coding techniques.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0031-3203 ISBN Medium
Area Expedition Conference
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ BGE2013a Serial 2247
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Author Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados; Thierry Brouard
Title Fuzzy Multilevel Graph Embedding Type Journal Article
Year 2013 Publication Pattern Recognition Abbreviated Journal PR
Volume 46 Issue 2 Pages 551-565
Keywords Pattern recognition; Graphics recognition; Graph clustering; Graph classification; Explicit graph embedding; Fuzzy logic
Abstract Structural pattern recognition approaches offer the most expressive, convenient, powerful but computational expensive representations of underlying relational information. To benefit from mature, less expensive and efficient state-of-the-art machine learning models of statistical pattern recognition they must be mapped to a low-dimensional vector space. Our method of explicit graph embedding bridges the gap between structural and statistical pattern recognition. We extract the topological, structural and attribute information from a graph and encode numeric details by fuzzy histograms and symbolic details by crisp histograms. The histograms are concatenated to achieve a simple and straightforward embedding of graph into a low-dimensional numeric feature vector. Experimentation on standard public graph datasets shows that our method outperforms the state-of-the-art methods of graph embedding for richly attributed graphs.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0031-3203 ISBN Medium
Area Expedition Conference
Notes DAG; 600.042; 600.045; 605.203 Approved no
Call Number Admin @ si @ LRL2013a Serial 2270
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Author Anjan Dutta; Josep Llados; Umapada Pal
Title A symbol spotting approach in graphical documents by hashing serialized graphs Type Journal Article
Year 2013 Publication Pattern Recognition Abbreviated Journal PR
Volume 46 Issue 3 Pages 752-768
Keywords Symbol spotting; Graphics recognition; Graph matching; Graph serialization; Graph factorization; Graph paths; Hashing
Abstract In this paper we propose a symbol spotting technique in graphical documents. Graphs are used to represent the documents and a (sub)graph matching technique is used to detect the symbols in them. We propose a graph serialization to reduce the usual computational complexity of graph matching. Serialization of graphs is performed by computing acyclic graph paths between each pair of connected nodes. Graph paths are one-dimensional structures of graphs which are less expensive in terms of computation. At the same time they enable robust localization even in the presence of noise and distortion. Indexing in large graph databases involves a computational burden as well. We propose a graph factorization approach to tackle this problem. Factorization is intended to create a unified indexed structure over the database of graphical documents. Once graph paths are extracted, the entire database of graphical documents is indexed in hash tables by locality sensitive hashing (LSH) of shape descriptors of the paths. The hashing data structure aims to execute an approximate k-NN search in a sub-linear time. We have performed detailed experiments with various datasets of line drawings and compared our method with the state-of-the-art works. The results demonstrate the effectiveness and efficiency of our technique.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0031-3203 ISBN Medium
Area Expedition Conference
Notes DAG; 600.042; 600.045; 605.203; 601.152 Approved no
Call Number Admin @ si @ DLP2012 Serial 2127
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Author Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga
Title Low-level SpatioChromatic Grouping for Saliency Estimation Type Journal Article
Year 2013 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI
Volume 35 Issue 11 Pages 2810-2816
Keywords
Abstract We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics.
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 (up) 0162-8828 ISBN Medium
Area Expedition Conference
Notes CIC; 600.051; 600.052; 605.203 Approved no
Call Number Admin @ si @ MVO2013 Serial 2289
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Author Alex Pardo; Albert Clapes; Sergio Escalera; Oriol Pujol
Title Actions in Context: System for people with Dementia Type Conference Article
Year 2013 Publication 2nd International Workshop on Citizen Sensor Networks (Citisen2013) at the European Conference on Complex Systems Abbreviated Journal
Volume Issue Pages 3-14
Keywords Multi-modal data Fusion; Computer vision; Wearable sensors; Gesture recognition; Dementia
Abstract In the next forty years, the number of people living with dementia is expected to triple. In the last stages, people affected by this disease become dependent. This hinders the autonomy of the patient and has a huge social impact in time, money and effort. Given this scenario, we propose an ubiquitous system capable of recognizing daily specific actions. The system fuses and synchronizes data obtained from two complementary modalities – ambient and egocentric. The ambient approach consists in a fixed RGB-Depth camera for user and object recognition and user-object interaction, whereas the egocentric point of view is given by a personal area network (PAN) formed by a few wearable sensors and a smartphone, used for gesture recognition. The system processes multi-modal data in real-time, performing paralleled task recognition and modality synchronization, showing high performance recognizing subjects, objects, and interactions, showing its reliability to be applied in real case scenarios.
Address Barcelona; September 2013
Corporate Author Thesis
Publisher Springer International Publishing Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (up) 0302-9743 ISBN 978-3-319-04177-3 Medium
Area Expedition Conference ECCS
Notes HUPBA;MILAB Approved no
Call Number Admin @ si @ PCE2013 Serial 2354
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