toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
  Records Links (down)
Author Christophe Rigaud; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier edit  doi
isbn  openurl
  Title Color descriptor for content-based drawing retrieval Type Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 267 - 271  
  Keywords  
  Abstract 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.  
  Address Tours; Francia; April 2014  
  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 ISBN 978-1-4799-3243-6 Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.056; 600.077 Approved no  
  Call Number Admin @ si @ RKB2014 Serial 2479  
Permanent link to this record
 

 
Author Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades edit  doi
isbn  openurl
  Title Spotting Symbol Using Sparsity over Learned Dictionary of Local Descriptors Type Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 156-160  
  Keywords  
  Abstract 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.  
  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 ISBN 978-1-4799-3243-6 Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ DTR2014 Serial 2543  
Permanent link to this record
 

 
Author Dimosthenis Karatzas; Sergi Robles; Lluis Gomez edit   pdf
doi  isbn
openurl 
  Title An on-line platform for ground truthing and performance evaluation of text extraction systems Type Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 242 - 246  
  Keywords  
  Abstract 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.
 
  Address Tours; Francia; April 2014  
  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 ISBN 978-1-4799-3243-6 Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.056; 600.077 Approved no  
  Call Number Admin @ si @ KRG2014 Serial 2491  
Permanent link to this record
 

 
Author P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes edit   pdf
doi  isbn
openurl 
  Title A Novel Learning-free Word Spotting Approach Based on Graph Representation Type Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 207-211  
  Keywords  
  Abstract 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.  
  Address Tours; France; April 2014  
  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 ISBN 978-1-4799-3243-6 Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ WEG2014b Serial 2517  
Permanent link to this record
 

 
Author David Fernandez; R.Manmatha; Josep Llados; Alicia Fornes edit   pdf
doi  isbn
openurl 
  Title Sequential Word Spotting in Historical Handwritten Documents Type Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 101 - 105  
  Keywords  
  Abstract 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.
 
  Address Tours; Francia; April 2014  
  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 ISBN 978-1-4799-3243-6 Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.061; 600.056; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ FML2014 Serial 2462  
Permanent link to this record
 

 
Author Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier edit  doi
isbn  openurl
  Title Combining Focus Measure Operators to Predict OCR Accuracy in Mobile-Captured Document Images Type Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 181 - 185  
  Keywords  
  Abstract 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.  
  Address Tours; France; April 2014  
  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 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
 

 
Author Albert Gordo; Florent Perronnin; Ernest Valveny edit   pdf
doi  isbn
openurl 
  Title Document classification using multiple views Type Conference Article
  Year 2012 Publication 10th IAPR International Workshop on Document Analysis Systems Abbreviated Journal  
  Volume Issue Pages 33-37  
  Keywords  
  Abstract The combination of multiple features or views when representing documents or other kinds of objects usually leads to improved results in classification (and retrieval) tasks. Most systems assume that those views will be available both at training and test time. However, some views may be too `expensive' to be available at test time. In this paper, we consider the use of Canonical Correlation Analysis to leverage `expensive' views that are available only at training time. Experimental results show that this information may significantly improve the results in a classification task.  
  Address Australia  
  Corporate Author Thesis  
  Publisher IEEE Computer Society Washington Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-0-7695-4661-2 Medium  
  Area Expedition Conference DAS  
  Notes DAG Approved no  
  Call Number Admin @ si @ GPV2012 Serial 2049  
Permanent link to this record
 

 
Author Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke edit  doi
openurl 
  Title Writer Identification in Old Handwritten Music Scores Type Book Chapter
  Year 2012 Publication Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology Abbreviated Journal  
  Volume Issue Pages 27-63  
  Keywords  
  Abstract The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores. Even though an important amount of compositions contains handwritten text in the music scores, the aim of our work is to use only music notation to determine the author. The steps of the system proposed are the following. First of all, the music sheet is preprocessed and normalized for obtaining a single binarized music line, without the staff lines. Afterwards, 100 features are extracted for every music line, which are subsequently used in a k-NN classifier that compares every feature vector with prototypes stored in a database. By applying feature selection and extraction methods on the original feature set, the performance is increased. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving a recognition rate of about 95%.  
  Address  
  Corporate Author Thesis  
  Publisher IGI-Global Place of Publication Editor Copnstantin Papaodysseus  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ FLS2012 Serial 1828  
Permanent link to this record
 

 
Author Dena Bazazian; Dimosthenis Karatzas; Andrew Bagdanov edit   pdf
doi  openurl
  Title Word Spotting in Scene Images based on Character Recognition Type Conference Article
  Year 2018 Publication IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops Abbreviated Journal  
  Volume Issue Pages 1872-1874  
  Keywords  
  Abstract In this paper we address the problem of unconstrained Word Spotting in scene images. We train a Fully Convolutional Network to produce heatmaps of all the character classes. Then, we employ the Text Proposals approach and, via a rectangle classifier, detect the most likely rectangle for each query word based on the character attribute maps. We evaluate the proposed method on ICDAR2015 and show that it is capable of identifying and recognizing query words in natural scene images.  
  Address Salt Lake City; USA; June 2018  
  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 ISBN Medium  
  Area Expedition Conference CVPRW  
  Notes DAG; 600.129; 600.121 Approved no  
  Call Number BKB2018a Serial 3179  
Permanent link to this record
 

 
Author Ilke Demir; Dena Bazazian; Adriana Romero; Viktoriia Sharmanska; Lyne P. Tchapmi edit   pdf
doi  openurl
  Title WiCV 2018: The Fourth Women In Computer Vision Workshop Type Conference Article
  Year 2018 Publication 4th Women in Computer Vision Workshop Abbreviated Journal  
  Volume Issue Pages 1941-19412  
  Keywords Conferences; Computer vision; Industries; Object recognition; Engineering profession; Collaboration; Machine learning  
  Abstract We present WiCV 2018 – Women in Computer Vision Workshop to increase the visibility and inclusion of women researchers in computer vision field, organized in conjunction with CVPR 2018. Computer vision and machine learning have made incredible progress over the past years, yet the number of female researchers is still low both in academia and industry. WiCV is organized to raise visibility of female researchers, to increase the collaboration,
and to provide mentorship and give opportunities to femaleidentifying junior researchers in the field. In its fourth year, we are proud to present the changes and improvements over the past years, summary of statistics for presenters and attendees, followed by expectations from future generations.
 
  Address Salt Lake City; USA; June 2018  
  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 ISBN Medium  
  Area Expedition Conference WiCV  
  Notes DAG; 600.121; 600.129 Approved no  
  Call Number Admin @ si @ DBR2018 Serial 3222  
Permanent link to this record
Select All    Deselect All
 |   | 
Details

Save Citations:
Export Records: