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Author |
Jorge Bernal; David Vazquez (eds) |
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Title |
Computer vision Trends and Challenges |
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Book Whole |
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Year |
2013 |
Publication |
Computer vision Trends and Challenges |
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CVCRD; Computer Vision |
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This book contains the papers presented at the Eighth CVC Workshop on Computer Vision Trends and Challenges (CVCR&D'2013). The workshop was held at the Computer Vision Center (Universitat Autònoma de Barcelona), the October 25th, 2013. The CVC workshops provide an excellent opportunity for young researchers and project engineers to share new ideas and knowledge about the progress of their work, and also, to discuss about challenges and future perspectives. In addition, the workshop is the welcome event for new people that recently have joined the institute.
The program of CVCR&D is organized in a single-track single-day workshop. It comprises several sessions dedicated to specific topics. For each session, a doctor working on the topic introduces the general research lines. The PhD students expose their specific research. A poster session will be held for open questions. Session topics cover the current research lines and development projects of the CVC: Medical Imaging, Medical Imaging, Color & Texture Analysis, Object Recognition, Image Sequence Evaluation, Advanced Driver Assistance Systems, Machine Vision, Document Analysis, Pattern Recognition and Applications. We want to thank all paper authors and Program Committee members. Their contribution shows that the CVC has a dynamic, active, and promising scientific community.
We hope you all enjoy this Eighth workshop and we are looking forward to meeting you and new people next year in the Ninth CVCR&D. |
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Jorge Bernal; David Vazquez |
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978-84-940902-2-6 |
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ADAS @ adas @ BeV2013 |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2339 |
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Author |
Jiaolong Xu; Sebastian Ramos; Xu Hu; David Vazquez; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Multi-task Bilinear Classifiers for Visual Domain Adaptation |
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Conference Article |
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Year |
2013 |
Publication |
Advances in Neural Information Processing Systems Workshop |
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Domain Adaptation; Pedestrian Detection; ADAS |
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We propose a method that aims to lessen the significant accuracy degradation
that a discriminative classifier can suffer when it is trained in a specific domain (source domain) and applied in a different one (target domain). The principal reason for this degradation is the discrepancies in the distribution of the features that feed the classifier in different domains. Therefore, we propose a domain adaptation method that maps the features from the different domains into a common subspace and learns a discriminative domain-invariant classifier within it. Our algorithm combines bilinear classifiers and multi-task learning for domain adaptation.
The bilinear classifier encodes the feature transformation and classification
parameters by a matrix decomposition. In this way, specific feature transformations for multiple domains and a shared classifier are jointly learned in a multi-task learning framework. Focusing on domain adaptation for visual object detection, we apply this method to the state-of-the-art deformable part-based model for cross domain pedestrian detection. Experimental results show that our method significantly avoids the domain drift and improves the accuracy when compared to several baselines. |
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Lake Tahoe; Nevada; USA; December 2013 |
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NIPSW |
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ADAS; 600.054; 600.057; 601.217;ISE |
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ADAS @ adas @ XRH2013 |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2340 |
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Author |
Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol |
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Title |
Interactive Document Retrieval and Classification. |
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Book Chapter |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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48 |
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17-30 |
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In this chapter we describe a system for document retrieval and classification following the interactive-predictive framework. In particular, the system addresses two different scenarios of document analysis: document classification based on visual appearance and logo detection. These two classical problems of document analysis are formulated following the interactive-predictive model, taking the user interaction into account to make easier the process of annotating and labelling the documents. A system implementing this model in a real scenario is presented and analyzed. This system also takes advantage of active learning techniques to speed up the task of labelling the documents. |
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Springer Berlin Heidelberg |
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Angel Sappa; Jordi Vitria |
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1868-4394 |
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978-3-642-35931-6 |
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DAG |
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no |
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Admin @ si @ VRM2013 |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2341 |
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Author |
L. Rothacker; Marçal Rusiñol; G.A. Fink |
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Title |
Bag-of-Features HMMs for segmentation-free word spotting in handwritten documents |
Type |
Conference Article |
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Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
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1305 - 1309 |
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Recent HMM-based approaches to handwritten word spotting require large amounts of learning samples and mostly rely on a prior segmentation of the document. We propose to use Bag-of-Features HMMs in a patch-based segmentation-free framework that are estimated by a single sample. Bag-of-Features HMMs use statistics of local image feature representatives. Therefore they can be considered as a variant of discrete HMMs allowing to model the observation of a number of features at a point in time. The discrete nature enables us to estimate a query model with only a single example of the query provided by the user. This makes our method very flexible with respect to the availability of training data. Furthermore, we are able to outperform state-of-the-art results on the George Washington dataset. |
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Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
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DAG |
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no |
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Call Number |
Admin @ si @ RRF2013 |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2344 |
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Author |
Albert Gordo; Marçal Rusiñol; Dimosthenis Karatzas; Andrew Bagdanov |
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Title |
Document Classification and Page Stream Segmentation for Digital Mailroom Applications |
Type |
Conference Article |
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Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
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Pages |
621-625 |
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In this paper we present a method for the segmentation of continuous page streams into multipage documents and the simultaneous classification of the resulting documents. We first present an approach to combine the multiple pages of a document into a single feature vector that represents the whole document. Despite its simplicity and low computational cost, the proposed representation yields results comparable to more complex methods in multipage document classification tasks. We then exploit this representation in the context of page stream segmentation. The most plausible segmentation of a page stream into a sequence of multipage documents is obtained by optimizing a statistical model that represents the probability of each segmented multipage document belonging to a particular class. Experimental results are reported on a large sample of real administrative multipage documents. |
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Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
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DAG; 600.056; 602.101 |
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no |
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Call Number |
Admin @ si @ GRK2013c |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2345 |
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Author |
Marçal Rusiñol; T.Benkhelfallah; V. Poulain d'Andecy |
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Title |
Field Extraction from Administrative Documents by Incremental Structural Templates |
Type |
Conference Article |
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Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
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Pages |
1100 - 1104 |
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In this paper we present an incremental framework aimed at extracting field information from administrative document images in the context of a Digital Mail-room scenario. Given a single training sample in which the user has marked which fields have to be extracted from a particular document class, a document model representing structural relationships among words is built. This model is incrementally refined as the system processes more and more documents from the same class. A reformulation of the tf-idf statistic scheme allows to adjust the importance weights of the structural relationships among words. We report in the experimental section our results obtained with a large dataset of real invoices. |
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Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
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DAG; 600.56; 600.045; 605.203; 602.101 |
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no |
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Call Number |
Admin @ si @ RBP2013 |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2346 |
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Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
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Title |
Spotting Graphical Symbols in Camera-Acquired Documents in Real Time |
Type |
Conference Article |
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Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
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In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time. |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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Notes |
DAG; 600.045; 600.055; 600.061; 602.101 |
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no |
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Call Number |
Admin @ si @ RKL2013 |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2347 |
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Author |
Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Classification of Administrative Document Images by Logo Identification |
Type |
Conference Article |
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Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
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This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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DAG; 600.056; 600.045; 605.203 |
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no |
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Admin @ si @ |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2348 |
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Author |
Francesco Ciompi; Rui Hua; Simone Balocco; Marina Alberti; Oriol Pujol; Carles Caus; J. Mauri; Petia Radeva |
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Title |
Learning to Detect Stent Struts in Intravascular Ultrasound |
Type |
Conference Article |
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Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
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Volume |
7887 |
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575-583 |
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In this paper we tackle the automatic detection of struts elements (metallic braces of a stent device) in Intravascular Ultrasound (IVUS) sequences. The proposed method is based on context-aware classification of IVUS images, where we use Multi-Class Multi-Scale Stacked Sequential Learning (M2SSL). Additionally, we introduce a novel technique to reduce the amount of required contextual features. The comparison with binary and multi-class learning is also performed, using a dataset of IVUS images with struts manually annotated by an expert. The best performing configuration reaches a F-measure F = 63.97% . |
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Madeira; Portugal; June 2013 |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-38627-5 |
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IbPRIA |
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MILAB; HuPBA; 605.203; 600.046 |
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no |
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Admin @ si @ CHB2013 |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2349 |
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Permanent link to this record |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality |
Type |
Conference Article |
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Year |
2013 |
Publication |
ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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624-631 |
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Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field. |
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Sydney; Australia; December 2013 |
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CVTT:E2M |
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IAM; ADAS; 600.044; 600.057; 601.145 |
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no |
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Call Number |
Admin @ si @ MGH2013b |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2351 |
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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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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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HUPBA;MILAB |
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no |
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Admin @ si @ PCE2013 |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2354 |
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Author |
S.Grau; Ana Puig; Sergio Escalera; Maria Salamo |
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Title |
Intelligent Interactive Volume Classification |
Type |
Conference Article |
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Year |
2013 |
Publication |
Pacific Graphics |
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Volume |
32 |
Issue |
7 |
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23-28 |
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This paper defines an intelligent and interactive framework to classify multiple regions of interest from the original data on demand, without requiring any preprocessing or previous segmentation. The proposed intelligent and interactive approach is divided in three stages: visualize, training and testing. First, users visualize and label some samples directly on slices of the volume. Training and testing are based on a framework of Error Correcting Output Codes and Adaboost classifiers that learn to classify each region the user has painted. Later, at the testing stage, each classifier is directly applied on the rest of samples and combined to perform multi-class labeling, being used in the final rendering. We also parallelized the training stage using a GPU-based implementation for
obtaining a rapid interaction and classification. |
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978-3-905674-50-7 |
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PG |
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HuPBA; 600.046;MILAB |
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Admin @ si @ GPE2013b |
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2355 |
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Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Near Convex Region Adjacency Graph and Approximate Neighborhood String Matching for Symbol Spotting in Graphical Documents |
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Conference Article |
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2013 |
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12th International Conference on Document Analysis and Recognition |
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1078-1082 |
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This paper deals with a subgraph matching problem in Region Adjacency Graph (RAG) applied to symbol spotting in graphical documents. RAG is a very important, efficient and natural way of representing graphical information with a graph but this is limited to cases where the information is well defined with perfectly delineated regions. What if the information we are interested in is not confined within well defined regions? This paper addresses this particular problem and solves it by defining near convex grouping of oriented line segments which results in near convex regions. Pure convexity imposes hard constraints and can not handle all the cases efficiently. Hence to solve this problem we have defined a new type of convexity of regions, which allows convex regions to have concavity to some extend. We call this kind of regions Near Convex Regions (NCRs). These NCRs are then used to create the Near Convex Region Adjacency Graph (NCRAG) and with this representation we have formulated the problem of symbol spotting in graphical documents as a subgraph matching problem. For subgraph matching we have used the Approximate Edit Distance Algorithm (AEDA) on the neighborhood string, which starts working after finding a key node in the input or target graph and iteratively identifies similar nodes of the query graph in the neighborhood of the key node. The experiments are performed on artificial, real and distorted datasets. |
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Washington; USA; August 2013 |
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1520-5363 |
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DAG; 600.045; 600.056; 600.061; 601.152 |
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Admin @ si @ DLB2013a |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2358 |
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Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
![download PDF file pdf](img/file_PDF.gif)
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Title |
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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DAG |
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Admin @ si @ DLB2013b |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2359 |
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Author |
Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Plausibility-Graphs for Symbol Spotting in Graphical Documents |
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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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Graph representation of graphical documents often suffers from noise viz. spurious nodes and spurios edges of graph and their discontinuity etc. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance.
But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical
graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset. |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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DAG; 600.045; 600.056; 600.061; 601.152 |
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Admin @ si @ BDJ2013 |
Serial ![sorted by Serial field, ascending order (up)](img/sort_asc.gif) |
2360 |
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