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Author |
Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Apostolos Antonacopoulos; Josep Llados |
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Title |
An interactive appearance-based document retrieval system for historical newspapers |
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Conference Article |
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Year |
2013 |
Publication |
Proceedings of the International Conference on Computer Vision Theory and Applications |
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84-87 |
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In this paper we present a retrieval-based application aimed at assisting a user to semi-automatically segment an incoming flow of historical newspaper images by automatically detecting a particular type of pages based on their appearance. A visual descriptor is used to assess page similarity while a relevance feedback process allow refining the results iteratively. The application is tested on a large dataset of digitised historic newspapers. |
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Barcelona; February 2013 |
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VISAPP |
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Notes |
DAG; 600.056; 600.045; 605.203 |
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no |
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Call Number |
Admin @ si @ GRK2013a |
Serial |
2290 |
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Permanent link to this record |
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Author |
Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria |
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Title |
An Application for Efficient Error-Free Labeling of Medical Images |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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Volume |
48 |
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1-16 |
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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. |
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Springer Berlin Heidelberg |
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1868-4394 |
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978-3-642-35931-6 |
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MILAB; OR;MV |
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no |
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Admin @ si @ DSR2013 |
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2235 |
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Author |
Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier |
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Title |
An active contour model for speech balloon detection in comics |
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Conference Article |
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Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
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1240-1244 |
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Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent comic book understanding would enable a variety of new applications, including content-based retrieval and content retargeting. Document understanding in this domain is challenging as comics are semi-structured documents, combining semantically important graphical and textual parts. Few studies have been done in this direction. In this work we detail a novel approach for closed and non-closed speech balloon localization in scanned comic book pages, an essential step towards a fully automatic comic book understanding. The approach is compared with existing methods for closed balloon localization found in the literature and results are presented. |
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washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
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DAG; CIC; 600.056 |
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no |
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Admin @ si @ RKW2013a |
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2260 |
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Author |
Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers |
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Title |
Adapting Pedestrian Detection from Synthetic to Far Infrared Images |
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Conference Article |
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Year |
2013 |
Publication |
ICCV Workshop on Visual Domain Adaptation and Dataset Bias |
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Domain Adaptation; Far Infrared; Pedestrian Detection |
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We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes. |
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Sydney; Australia; December 2013 |
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Sydney, Australy |
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English |
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ICCVW-VisDA |
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ADAS; 600.054; 600.055; 600.057; 601.217;ISE |
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no |
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ADAS @ adas @ SRV2013 |
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2334 |
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Author |
Jiaolong Xu; David Vazquez; Sebastian Ramos; Antonio Lopez; Daniel Ponsa |
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Title |
Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers |
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Conference Article |
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Year |
2013 |
Publication |
CVPR Workshop on Ground Truth – What is a good dataset? |
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Pages |
688 - 693 |
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Keywords |
Pedestrian Detection; Domain Adaptation |
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Abstract |
Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%. |
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Portland; oregon; June 2013 |
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English |
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English |
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CVPRW |
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Notes |
ADAS; 600.054; 600.057; 601.217 |
Approved |
yes |
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Call Number |
XVR2013; ADAS @ adas @ xvr2013a |
Serial |
2220 |
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Author |
Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva |
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Title |
Adaptable image cuts for motility inspection using WCE |
Type |
Journal Article |
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Year |
2013 |
Publication |
Computerized Medical Imaging and Graphics |
Abbreviated Journal |
CMIG |
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Volume |
37 |
Issue |
1 |
Pages |
72-80 |
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Abstract |
The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE. |
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Notes |
MILAB; OR; 600.046; 605.203 |
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no |
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Call Number |
Admin @ si @ DSM2012 |
Serial |
2151 |
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Author |
Gemma Roig; Xavier Boix; R. de Nijs; Sebastian Ramos; K. Kühnlenz; Luc Van Gool |
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Title |
Active MAP Inference in CRFs for Efficient Semantic Segmentation |
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Conference Article |
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Year |
2013 |
Publication |
15th IEEE International Conference on Computer Vision |
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Pages |
2312 - 2319 |
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Keywords |
Semantic Segmentation |
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Most MAP inference algorithms for CRFs optimize an energy function knowing all the potentials. In this paper, we focus on CRFs where the computational cost of instantiating the potentials is orders of magnitude higher than MAP inference. This is often the case in semantic image segmentation, where most potentials are instantiated by slow classifiers fed with costly features. We introduce Active MAP inference 1) to on-the-fly select a subset of potentials to be instantiated in the energy function, leaving the rest of the parameters of the potentials unknown, and 2) to estimate the MAP labeling from such incomplete energy function. Results for semantic segmentation benchmarks, namely PASCAL VOC 2010 [5] and MSRC-21 [19], show that Active MAP inference achieves similar levels of accuracy but with major efficiency gains. |
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Sydney; Australia; December 2013 |
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1550-5499 |
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ICCV |
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Notes |
ADAS; 600.057 |
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no |
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Call Number |
ADAS @ adas @ RBN2013 |
Serial |
2377 |
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Author |
Marc Bolaños; Maite Garolera; Petia Radeva |
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Title |
Active labeling application applied to food-related object recognition |
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Conference Article |
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Year |
2013 |
Publication |
5th International Workshop on Multimedia for Cooking & Eating Activities |
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45-50 |
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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]. |
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Barcelona; October 2013 |
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ACM-CEA |
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Notes |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ BGR2013b |
Serial |
2637 |
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Permanent link to this record |
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Author |
Alex Pardo; Albert Clapes; Sergio Escalera; Oriol Pujol |
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Title |
Actions in Context: System for people with Dementia |
Type |
Conference Article |
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Year |
2013 |
Publication |
2nd International Workshop on Citizen Sensor Networks (Citisen2013) at the European Conference on Complex Systems |
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3-14 |
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Multi-modal data Fusion; Computer vision; Wearable sensors; Gesture recognition; Dementia |
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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. |
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Barcelona; September 2013 |
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Springer International Publishing |
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0302-9743 |
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978-3-319-04177-3 |
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ECCS |
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Notes |
HUPBA;MILAB |
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no |
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Call Number |
Admin @ si @ PCE2013 |
Serial |
2354 |
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Author |
Debora Gil; Agnes Borras; Sergio Vera; Miguel Angel Gonzalez Ballester |
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Title |
A Validation Benchmark for Assessment of Medial Surface Quality for Medical Applications |
Type |
Conference Article |
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Year |
2013 |
Publication |
9th International Conference on Computer Vision Systems |
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7963 |
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334-343 |
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Medial Surfaces; Shape Representation; Medical Applications; Performance Evaluation |
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Confident use of medial surfaces in medical decision support systems requires evaluating their quality for detecting pathological deformations and describing anatomical volumes. Validation in the medical imaging field is a challenging task mainly due to the difficulties for getting consensual ground truth. In this paper we propose a validation benchmark for assessing medial surfaces in the context of medical applications. Our benchmark includes a home-made database of synthetic medial surfaces and volumes and specific scores for evaluating surface accuracy, its stability against volume deformations and its capabilities for accurate reconstruction of anatomical volumes. |
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Sant Petersburg; Russia; July 2013 |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-39401-0 |
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ICVS |
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Notes |
IAM; 600.044; 600.060 |
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no |
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Admin @ si @ GBV2013 |
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2300 |
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Author |
R. Bertrand; P. Gomez-Krämer; Oriol Ramos Terrades; P. Franco; Jean-Marc Ogier |
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Title |
A System Based On Intrinsic Features for Fraudulent Document Detection |
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Conference Article |
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Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
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106-110 |
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paper document; document analysis; fraudulent document; forgery; fake |
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Paper documents still represent a large amount of information supports used nowadays and may contain critical data. Even though official documents are secured with techniques such as printed patterns or artwork, paper documents suffer froma lack of security.
However, the high availability of cheap scanning and printing hardware allows non-experts to easily create fake documents. As the use of a watermarking system added during the document production step is hardly possible, solutions have to be proposed to distinguish a genuine document from a forged one.
In this paper, we present an automatic forgery detection method based on document’s intrinsic features at character level. This method is based on the one hand on outlier character detection in a discriminant feature space and on the other hand on the detection of strictly similar characters. Therefore, a feature set iscomputed for all characters. Then, based on a distance between characters of the same class. |
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Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
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Notes |
DAG; 600.061 |
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no |
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Admin @ si @ BGR2013a |
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2332 |
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Permanent link to this record |
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Author |
Anjan Dutta; Josep Llados; Umapada Pal |
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Title |
A symbol spotting approach in graphical documents by hashing serialized graphs |
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Journal Article |
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2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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46 |
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3 |
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752-768 |
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Symbol spotting; Graphics recognition; Graph matching; Graph serialization; Graph factorization; Graph paths; Hashing |
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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. |
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Elsevier |
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0031-3203 |
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DAG; 600.042; 600.045; 605.203; 601.152 |
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no |
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Admin @ si @ DLP2012 |
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2127 |
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Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
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A Product graph based method for dual subgraph matching applied to symbol spotting |
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Conference Article |
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2013 |
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10th IAPR International Workshop on Graphics Recognition |
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Product graph has been shown to be an efficient way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. This paper focuses on the two major limitations of the previous version of product graph: (1) Spurious nodes and edges in the graph representation and (2) Inefficient node and edge attributes. To deal with noisy information of vectorized graphical documents, we consider a dual graph representation on the original graph representing the graphical information and the product graph is computed between the dual graphs of the query graphs and the input graph.
The dual graph with redundant edges is helpful for efficient and tolerating encoding of the structural information of the graphical documents. The adjacency matrix of the product graph locates similar path information of two graphs and exponentiating the adjacency matrix finds similar paths of greater lengths. Nodes joining similar paths between two graphs are found by combining different exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging. |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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Admin @ si @ DLB2013b |
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2359 |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
A Novel Space Variant Image Representation |
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Journal Article |
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2013 |
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Journal of Mathematical Imaging and Vision |
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JMIV |
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47 |
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1-2 |
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48-59 |
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Space-variant representation; Log-polar mapping; Onboard vision applications |
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Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences. |
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Springer US |
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0924-9907 |
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ADAS; 600.055; 605.203; 601.215 |
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Admin @ si @ OnS2013a |
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2243 |
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A. M. Here; B. C. Lopez; Debora Gil; J. J. Camarero; Jordi Martinez-Vilalta |
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A new software to analyse wood anatomical features in conifer species |
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2013 |
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International Symposium on Wood Structure in Plant Biology and Ecology |
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International Symposium on Wood Structure in Plant Biology and Ecology |
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Naples; Italy; March 2013 |
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WSE |
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IAM |
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Admin @ si @ HLG2013 |
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2303 |
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