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Author |
Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen |
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Title |
Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging |
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Conference Article |
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Year |
2014 |
Publication |
17th International Conference on Medical Image Computing and Computer Assisted Intervention |
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Volume |
8896 |
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231-238 |
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Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging |
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Abstract |
Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across dierent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three dierent OF methods, including HARP. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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0302-9743 |
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978-3-319-14677-5 |
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STACOM |
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IAM; ADAS; 600.060; 601.145; 600.076; 600.075 |
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Admin @ si @ MKF2014 |
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2495 |
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Author |
Maedeh Aghaei; Petia Radeva |
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Title |
Bag-of-Tracklets for Person Tracking in Life-Logging Data |
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Conference Article |
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Year |
2014 |
Publication |
17th International Conference of the Catalan Association for Artificial Intelligence |
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269 |
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35-44 |
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By increasing popularity of wearable cameras, life-logging data analysis is becoming more and more important and useful to derive significant events out of this substantial collection of images. In this study, we introduce a new tracking method applied to visual life-logging, called bag-of-tracklets, which is based on detecting, localizing and tracking of people. Given the low spatial and temporal resolution of the image data, our model generates and groups tracklets in a unsupervised framework and extracts image sequences of person appearance according to a similarity score of the bag-of-tracklets. The model output is a meaningful sequence of events expressing human appearance and tracking them in life-logging data. The achieved results prove the robustness of our model in terms of efficiency and accuracy despite the low spatial and temporal resolution of the data. |
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978-1-61499-451-0 |
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CCIA |
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MILAB |
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Admin @ si @ AgR2015 |
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2607 |
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Author |
Agata Lapedriza; David Masip; David Sanchez |
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Title |
Emotions Classification using Facial Action Units Recognition |
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Conference Article |
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Year |
2014 |
Publication |
17th International Conference of the Catalan Association for Artificial Intelligence |
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269 |
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55-64 |
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In this work we build a system for automatic emotion classification from image sequences. We analyze subtle changes in facial expressions by detecting a subset of 12 representative facial action units (AUs). Then, we classify emotions based on the output of these AUs classifiers, i.e. the presence/absence of AUs. We base the AUs classification upon a set of spatio-temporal geometric and appearance features for facial representation, fusing them within the emotion classifier. A decision tree is trained for emotion classifying, making the resulting model easy to interpret by capturing the combination of AUs activation that lead to a particular emotion. For Cohn-Kanade database, the proposed system classifies 7 emotions with a mean accuracy of near 90%, attaining a similar recognition accuracy in comparison with non-interpretable models that are not based in AUs detection. |
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978-1-61499-451-0 |
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CCIA |
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OR;MV |
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Admin @ si @ LMS2014 |
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2622 |
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Author |
David Fernandez; Pau Riba; Alicia Fornes; Josep Llados |
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Title |
On the Influence of Key Point Encoding for Handwritten Word Spotting |
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Conference Article |
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Year |
2014 |
Publication |
14th International Conference on Frontiers in Handwriting Recognition |
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476 - 481 |
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Keywords |
Local descriptors; Interest points; Handwritten documents; Word spotting; Historical document analysis |
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In this paper we evaluate the influence of the selection of key points and the associated features in the performance of word spotting processes. In general, features can be extracted from a number of characteristic points like corners, contours, skeletons, maxima, minima, crossings, etc. A number of descriptors exist in the literature using different interest point detectors. But the intrinsic variability of handwriting vary strongly on the performance if the interest points are not stable enough. In this paper, we analyze the performance of different descriptors for local interest points. As benchmarking dataset we have used the Barcelona Marriage Database that contains handwritten records of marriages over five centuries. |
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Creete Island; Grecia; September 2014 |
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2167-6445 |
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978-1-4799-4335-7 |
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ICFHR |
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DAG; 600.056; 600.061; 602.006; 600.077 |
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Admin @ si @ FRF2014 |
Serial |
2460 |
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Author |
Pau Riba; Jon Almazan; Alicia Fornes; David Fernandez; Ernest Valveny; Josep Llados |
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Title |
e-Crowds: a mobile platform for browsing and searching in historical demographyrelated manuscripts |
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Conference Article |
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Year |
2014 |
Publication |
14th International Conference on Frontiers in Handwriting Recognition |
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228 - 233 |
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This paper presents a prototype system running on portable devices for browsing and word searching through historical handwritten document collections. The platform adapts the paradigm of eBook reading, where the narrative is not necessarily sequential, but centered on the user actions. The novelty is to replace digitally born books by digitized historical manuscripts of marriage licenses, so document analysis tasks are required in the browser. With an active reading paradigm, the user can cast queries of people names, so he/she can implicitly follow genealogical links. In addition, the system allows combined searches: the user can refine a search by adding more words to search. As a second contribution, the retrieval functionality involves as a core technology a word spotting module with an unified approach, which allows combined query searches, and also two input modalities: query-by-example, and query-by-string. |
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Creete Island; Grecia; September 2014 |
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2167-6445 |
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978-1-4799-4335-7 |
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ICFHR |
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Notes |
DAG; 600.056; 600.045; 600.061; 602.006; 600.077 |
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no |
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Call Number |
Admin @ si @ RAF2014 |
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2463 |
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Author |
Francesco Brughi; Debora Gil; Llorenç Badiella; Eva Jove Casabella; Oriol Ramos Terrades |
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Title |
Exploring the impact of inter-query variability on the performance of retrieval systems |
Type |
Conference Article |
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Year |
2014 |
Publication |
11th International Conference on Image Analysis and Recognition |
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Volume |
8814 |
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Pages |
413–420 |
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This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes. |
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Algarve; Portugal; October 2014 |
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Springer International Publishing |
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0302-9743 |
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978-3-319-11757-7 |
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ICIAR |
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Notes |
IAM; DAG; 600.060; 600.061; 600.077; 600.075 |
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no |
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Admin @ si @ BGB2014 |
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2559 |
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Author |
E. Bondi ; L. Sidenari; Andrew Bagdanov; Alberto del Bimbo |
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Title |
Real-time people counting from depth imagery of crowded environments |
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Conference Article |
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2014 |
Publication |
11th IEEE International Conference on Advanced Video and Signal based Surveillance |
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337 - 342 |
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In this paper we describe a system for automatic people counting in crowded environments. The approach we propose is a counting-by-detection method based on depth imagery. It is designed to be deployed as an autonomous appliance for crowd analysis in video surveillance application scenarios. Our system performs foreground/background segmentation on depth image streams in order to coarsely segment persons, then depth information is used to localize head candidates which are then tracked in time on an automatically estimated ground plane. The system runs in real-time, at a frame-rate of about 20 fps. We collected a dataset of RGB-D sequences representing three typical and challenging surveillance scenarios, including crowds, queuing and groups. An extensive comparative evaluation is given between our system and more complex, Latent SVM-based head localization for person counting applications. |
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Seoul; Korea; August 2014 |
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AVSS |
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Notes |
LAMP; 600.079 |
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no |
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Admin @ si @ BSB2014 |
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2540 |
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Author |
David Fernandez; R.Manmatha; Josep Llados; Alicia Fornes |
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Title |
Sequential Word Spotting in Historical Handwritten Documents |
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Conference Article |
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2014 |
Publication |
11th IAPR International Workshop on Document Analysis and Systems |
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101 - 105 |
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In this work we present a handwritten word spotting approach that takes advantage of the a priori known order of appearance of the query words. Given an ordered sequence of query word instances, the proposed approach performs a
sequence alignment with the words in the target collection. Although the alignment is quite sparse, i.e. the number of words in the database is higher than the query set, the improvement in the overall performance is sensitively higher than isolated word spotting. As application dataset, we use a collection of handwritten marriage licenses taking advantage of the ordered
index pages of family names. |
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Tours; Francia; April 2014 |
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978-1-4799-3243-6 |
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DAS |
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DAG; 600.061; 600.056; 602.006; 600.077 |
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no |
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Admin @ si @ FML2014 |
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2462 |
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Author |
Christophe Rigaud; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier |
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Title |
Color descriptor for content-based drawing retrieval |
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Conference Article |
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2014 |
Publication |
11th IAPR International Workshop on Document Analysis and Systems |
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267 - 271 |
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Human detection in computer vision field is an active field of research. Extending this to human-like drawings such as the main characters in comic book stories is not trivial. Comics analysis is a very recent field of research at the intersection of graphics, texts, objects and people recognition. The detection of the main comic characters is an essential step towards a fully automatic comic book understanding. This paper presents a color-based approach for comics character retrieval using content-based drawing retrieval and color palette. |
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Tours; Francia; April 2014 |
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978-1-4799-3243-6 |
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DAG; 600.056; 600.077 |
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Admin @ si @ RKB2014 |
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2479 |
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Author |
Dimosthenis Karatzas; Sergi Robles; Lluis Gomez |
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An on-line platform for ground truthing and performance evaluation of text extraction systems |
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Conference Article |
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2014 |
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11th IAPR International Workshop on Document Analysis and Systems |
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242 - 246 |
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This paper presents a set of on-line software tools for creating ground truth and calculating performance evaluation metrics for text extraction tasks such as localization, segmentation and recognition. The platform supports the definition of comprehensive ground truth information at different text representation levels while it offers centralised management and quality control of the ground truthing effort. It implements a range of state of the art performance evaluation algorithms and offers functionality for the definition of evaluation scenarios, on-line calculation of various performance metrics and visualisation of the results. The
presented platform, which comprises the backbone of the ICDAR 2011 (challenge 1) and 2013 (challenges 1 and 2) Robust Reading competitions, is now made available for public use. |
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Tours; Francia; April 2014 |
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978-1-4799-3243-6 |
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DAG; 600.056; 600.077 |
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no |
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Admin @ si @ KRG2014 |
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2491 |
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Author |
P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes |
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A Novel Learning-free Word Spotting Approach Based on Graph Representation |
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Conference Article |
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2014 |
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11th IAPR International Workshop on Document Analysis and Systems |
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207-211 |
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Effective information retrieval on handwritten document images has always been a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. In order to be robust to the handwriting variations, an exhaustive merging process based on DTW alignment result is introduced in the similarity measure between word images. With respect to the computation complexity, an approximate graph edit distance approach using bipartite matching is employed for graph matching. The experiments on the George Washington dataset and the marriage records from the Barcelona Cathedral dataset demonstrate that the proposed approach outperforms the state-of-the-art structural methods. |
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Tours; France; April 2014 |
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978-1-4799-3243-6 |
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DAG; 600.061; 602.006; 600.077 |
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Admin @ si @ WEG2014b |
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2517 |
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Author |
Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades |
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Title |
Spotting Symbol Using Sparsity over Learned Dictionary of Local Descriptors |
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Conference Article |
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2014 |
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11th IAPR International Workshop on Document Analysis and Systems |
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156-160 |
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This paper proposes a new approach to spot symbols into graphical documents using sparse representations. More specifically, a dictionary is learned from a training database of local descriptors defined over the documents. Following their sparse representations, interest points sharing similar properties are used to define interest regions. Using an original adaptation of information retrieval techniques, a vector model for interest regions and for a query symbol is built based on its sparsity in a visual vocabulary where the visual words are columns in the learned dictionary. The matching process is performed comparing the similarity between vector models. Evaluation on SESYD datasets demonstrates that our method is promising. |
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978-1-4799-3243-6 |
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DAG; 600.077 |
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Admin @ si @ DTR2014 |
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2543 |
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Author |
Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier |
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Title |
Combining Focus Measure Operators to Predict OCR Accuracy in Mobile-Captured Document Images |
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Conference Article |
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2014 |
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11th IAPR International Workshop on Document Analysis and Systems |
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181 - 185 |
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Mobile document image acquisition is a new trend raising serious issues in business document processing workflows. Such digitization procedure is unreliable, and integrates many distortions which must be detected as soon as possible, on the mobile, to avoid paying data transmission fees, and losing information due to the inability to re-capture later a document with temporary availability. In this context, out-of-focus blur is major issue: users have no direct control over it, and it seriously degrades OCR recognition. In this paper, we concentrate on the estimation of focus quality, to ensure a sufficient legibility of a document image for OCR processing. We propose two contributions to improve OCR accuracy prediction for mobile-captured document images. First, we present 24 focus measures, never tested on document images, which are fast to compute and require no training. Second, we show that a combination of those measures enables state-of-the art performance regarding the correlation with OCR accuracy. The resulting approach is fast, robust, and easy to implement in a mobile device. Experiments are performed on a public dataset, and precise details about image processing are given. |
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Tours; France; April 2014 |
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Series Volume |
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Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-1-4799-3243-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
DAS |
|
|
Notes |
DAG; 601.223; 600.077 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RCO2014a |
Serial |
2545 |
|
Permanent link to this record |