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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Volumetric Anatomical Parameterization and Meshing for Inter-patient Liver Coordinate System Deffinition |
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Conference Article |
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Year |
2013 |
Publication |
16th International Conference on Medical Image Computing and Computer Assisted Intervention |
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Nagoya; Japan; September 2013 |
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MICCAI |
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IAM |
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no |
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Admin @ si @ VGG2013 |
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2301 |
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Author |
Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
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Title |
On-line lumen centre detection in gastrointestinal and respiratory endoscopy |
Type |
Conference Article |
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Year |
2013 |
Publication |
Second International Workshop Clinical Image-Based Procedures |
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Volume |
8361 |
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31-38 |
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Keywords |
Lumen centre detection; Bronchoscopy; Colonoscopy |
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Abstract |
We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %). |
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Nagoya; Japan; September 2013 |
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Springer International Publishing |
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Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus |
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LNCS |
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978-3-319-05665-4 |
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800 |
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CLIP |
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MV; IAM; 600.047; 600.044; 600.060 |
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no |
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Admin @ si @ SBG2013 |
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2302 |
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Author |
Volkmar Frinken; Andreas Fischer; Markus Baumgartner; Horst Bunke |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Keyword spotting for self-training of BLSTM NN based handwriting recognition systems |
Type |
Journal Article |
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Year |
2014 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
47 |
Issue |
3 |
Pages |
1073-1082 |
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Keywords |
Document retrieval; Keyword spotting; Handwriting recognition; Neural networks; Semi-supervised learning |
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Abstract |
The automatic transcription of unconstrained continuous handwritten text requires well trained recognition systems. The semi-supervised paradigm introduces the concept of not only using labeled data but also unlabeled data in the learning process. Unlabeled data can be gathered at little or not cost. Hence it has the potential to reduce the need for labeling training data, a tedious and costly process. Given a weak initial recognizer trained on labeled data, self-training can be used to recognize unlabeled data and add words that were recognized with high confidence to the training set for re-training. This process is not trivial and requires great care as far as selecting the elements that are to be added to the training set is concerned. In this paper, we propose to use a bidirectional long short-term memory neural network handwritten recognition system for keyword spotting in order to select new elements. A set of experiments shows the high potential of self-training for bootstrapping handwriting recognition systems, both for modern and historical handwritings, and demonstrate the benefits of using keyword spotting over previously published self-training schemes. |
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Notes |
DAG; 600.077; 602.101 |
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no |
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Call Number |
Admin @ si @ FFB2014 |
Serial |
2297 |
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Author |
Veronica Romero; Alicia Fornes; Nicolas Serrano; Joan Andreu Sanchez; A.H. Toselli; Volkmar Frinken; E. Vidal; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition |
Type |
Journal Article |
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Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
46 |
Issue |
6 |
Pages |
1658-1669 |
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Abstract |
Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demography studies and genealogical research. Automatic processing of historical documents, however, has mostly been focused on single works of literature and less on social records, which tend to have a distinct layout, structure, and vocabulary. Such information is usually collected by expert demographers that devote a lot of time to manually transcribe them. This paper presents a new database, compiled from a marriage license books collection, to support research in automatic handwriting recognition for historical documents containing social records. Marriage license books are documents that were used for centuries by ecclesiastical institutions to register marriage licenses. Books from this collection are handwritten and span nearly half a millennium until the beginning of the 20th century. In addition, a study is presented about the capability of state-of-the-art handwritten text recognition systems, when applied to the presented database. Baseline results are reported for reference in future studies. |
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Elsevier Science Inc. New York, NY, USA |
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0031-3203 |
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Notes |
DAG; 600.045; 602.006; 605.203 |
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no |
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Call Number |
Admin @ si @ RFS2013 |
Serial |
2298 |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Detecting loss of diversity for an efficient termination of EAs |
Type |
Conference Article |
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Year |
2013 |
Publication |
15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing |
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Pages |
561 - 566 |
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Keywords |
EA termination; EA population diversity; EA steady state |
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Abstract |
Termination of Evolutionary Algorithms (EA) at its steady state so that useless iterations are not performed is a main point for its efficient application to black-box problems. Many EA algorithms evolve while there is still diversity in their population and, thus, they could be terminated by analyzing the behavior some measures of EA population diversity. This paper presents a numeric approximation to steady states that can be used to detect the moment EA population has lost its diversity for EA termination. Our condition has been applied to 3 EA paradigms based on diversity and a selection of functions
covering the properties most relevant for EA convergence.
Experiments show that our condition works regardless of the search space dimension and function landscape. |
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Timisoara; Rumania; |
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978-1-4799-3035-7 |
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SYNASC |
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Notes |
IAM; 600.044; 600.060; 605.203 |
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no |
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Call Number |
Admin @ si @ RGG2013c |
Serial |
2299 |
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Author |
Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados; Tomokazu Sato; Masakazu Iwamura; Koichi Kise |
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Title |
Key-region detection for document images -applications to administrative document retrieval |
Type |
Conference Article |
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Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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Volume |
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Pages |
230-234 |
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Abstract |
In this paper we argue that a key-region detector designed to take into account the special characteristics of document images can result in the detection of less and more meaningful key-regions. We propose a fast key-region detector able to capture aspects of the structural information of the document, and demonstrate its efficiency by comparing against standard detectors in an administrative document retrieval scenario. We show that using the proposed detector results to a smaller number of detected key-regions and higher performance without any drop in speed compared to standard state of the art detectors. |
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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; 600.056; 600.045 |
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no |
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Call Number |
Admin @ si @ GRK2013b |
Serial |
2293 |
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Author |
Andreas Fischer; Ching Y. Suen; Volkmar Frinken; Kaspar Riesen; Horst Bunke |
![download PDF file pdf](img/file_PDF.gif)
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Title |
A Fast Matching Algorithm for Graph-Based Handwriting Recognition |
Type |
Conference Article |
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Year |
2013 |
Publication |
9th IAPR – TC15 Workshop on Graph-based Representation in Pattern Recognition |
Abbreviated Journal |
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Volume |
7877 |
Issue |
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Pages |
194-203 |
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Abstract |
The recognition of unconstrained handwriting images is usually based on vectorial representation and statistical classification. Despite their high representational power, graphs are rarely used in this field due to a lack of efficient graph-based recognition methods. Recently, graph similarity features have been proposed to bridge the gap between structural representation and statistical classification by means of vector space embedding. This approach has shown a high performance in terms of accuracy but had shortcomings in terms of computational speed. The time complexity of the Hungarian algorithm that is used to approximate the edit distance between two handwriting graphs is demanding for a real-world scenario. In this paper, we propose a faster graph matching algorithm which is derived from the Hausdorff distance. On the historical Parzival database it is demonstrated that the proposed method achieves a speedup factor of 12.9 without significant loss in recognition accuracy. |
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Vienna; Austria; May 2013 |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-38220-8 |
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GBR |
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Notes |
DAG; 600.045; 605.203 |
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no |
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Admin @ si @ FSF2013 |
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2294 |
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Author |
Andreas Fischer; Volkmar Frinken; Horst Bunke; Ching Y. Suen |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Improving HMM-Based Keyword Spotting with Character Language Models |
Type |
Conference Article |
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Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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Volume |
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Pages |
506-510 |
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Facing high error rates and slow recognition speed for full text transcription of unconstrained handwriting images, keyword spotting is a promising alternative to locate specific search terms within scanned document images. We have previously proposed a learning-based method for keyword spotting using character hidden Markov models that showed a high performance when compared with traditional template image matching. In the lexicon-free approach pursued, only the text appearance was taken into account for recognition. In this paper, we integrate character n-gram language models into the spotting system in order to provide an additional language context. On the modern IAM database as well as the historical George Washington database, we demonstrate that character language models significantly improve the spotting performance. |
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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; 600.045; 605.203 |
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no |
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Call Number |
Admin @ si @ FFB2013 |
Serial |
2295 |
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Permanent link to this record |
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Author |
Volkmar Frinken; Andreas Fischer; Carlos David Martinez Hinarejos |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Handwriting Recognition in Historical Documents using Very Large Vocabularies |
Type |
Conference Article |
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Year |
2013 |
Publication |
2nd International Workshop on Historical Document Imaging and Processing |
Abbreviated Journal |
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Issue |
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Pages |
67-72 |
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Language models are used in automatic transcription system to resolve ambiguities. This is done by limiting the vocabulary of words that can be recognized as well as estimating the n-gram probability of the words in the given text. In the context of historical documents, a non-unified spelling and the limited amount of written text pose a substantial problem for the selection of the recognizable vocabulary as well as the computation of the word probabilities. In this paper we propose for the transcription of historical Spanish text to keep the corpus for the n-gram limited to a sample of the target text, but expand the vocabulary with words gathered from external resources. We analyze the performance of such a transcription system with different sizes of external vocabularies and demonstrate the applicability and the significant increase in recognition accuracy of using up to 300 thousand external words. |
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Washington; USA; August 2013 |
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978-1-4503-2115-0 |
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HIP |
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DAG; 600.056; 600.045; 600.061; 602.006; 602.101 |
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no |
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Admin @ si @ FFM2013 |
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2296 |
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Author |
Antonio Clavelli; Dimosthenis Karatzas; Josep Llados; Mario Ferraro; Giuseppe Boccignone |
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Title |
Towards Modelling an Attention-Based Text Localization Process |
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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296-303 |
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text localization; visual attention; eye guidance |
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This note introduces a visual attention model of text localization in real-world scenes. The core of the model built upon the proto-object concept is discussed. It is shown how such dynamic mid-level representation of the scene can be derived in the framework of an action-perception loop engaging salience, text information value computation, and eye guidance mechanisms.
Preliminary results that compare model generated scanpaths with those eye-tracked from human subjects are presented. |
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Address |
Madeira; Portugal; June 2013 |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-38627-5 |
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IbPRIA |
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DAG |
Approved |
no |
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Admin @ si @ CKL2013 |
Serial |
2291 |
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Permanent link to this record |
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Author |
Nuria Cirera; Alicia Fornes; Volkmar Frinken; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Hybrid grammar language model for handwritten historical documents recognition |
Type |
Conference Article |
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Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
7887 |
Issue |
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Pages |
117-124 |
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Abstract |
In this paper we present a hybrid language model for the recognition of handwritten historical documents with a structured syntactical layout. Using a hidden Markov model-based recognition framework, a word-based grammar with a closed dictionary is enhanced by a character sequence recognition method. This allows to recognize out-of-dictionary words in controlled parts of the recognition, while keeping a closed vocabulary restriction for other parts. While the current status is work in progress, we can report an improvement in terms of character error rate. |
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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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Notes |
DAG; 602.006; 600.045; 600.061 |
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no |
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Call Number |
Admin @ si @ CFF2013 |
Serial |
2292 |
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Permanent link to this record |
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Author |
Joost Van de Weijer; Fahad Shahbaz Khan |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Fusing Color and Shape for Bag-of-Words Based Object Recognition |
Type |
Conference Article |
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Year |
2013 |
Publication |
4th Computational Color Imaging Workshop |
Abbreviated Journal |
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Volume |
7786 |
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Pages |
25-34 |
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Keywords |
Object Recognition; color features; bag-of-words; image classification |
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Abstract |
In this article we provide an analysis of existing methods for the incorporation of color in bag-of-words based image representations. We propose a list of desired properties on which bases fusing methods can be compared. We discuss existing methods and indicate shortcomings of the two well-known fusing methods, namely early and late fusion. Several recent works have addressed these shortcomings by exploiting top-down information in the bag-of-words pipeline: color attention which is motivated from human vision, and Portmanteau vocabularies which are based on information theoretic compression of product vocabularies. We point out several remaining challenges in cue fusion and provide directions for future research. |
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Address |
Chiba; Japan; March 2013 |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-36699-4 |
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CCIW |
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Notes |
CIC; 600.048 |
Approved |
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Admin @ si @ WeK2013 |
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2283 |
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Author |
Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
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Title |
Interactive Visual and Semantic Image Retrieval |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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Volume |
48 |
Issue |
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Pages |
31-35 |
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Abstract |
One direct consequence of recent advances in digital visual data generation and the direct availability of this information through the World-Wide Web, is a urgent demand for efficient image retrieval systems. The objective of image retrieval is to allow users to efficiently browse through this abundance of images. Due to the non-expert nature of the majority of the internet users, such systems should be user friendly, and therefore avoid complex user interfaces. In this chapter we investigate how high-level information provided by recently developed object recognition techniques can improve interactive image retrieval. Wel apply a bagof- word based image representation method to automatically classify images in a number of categories. These additional labels are then applied to improve the image retrieval system. Next to these high-level semantic labels, we also apply a low-level image description to describe the composition and color scheme of the scene. Both descriptions are incorporated in a user feedback image retrieval setting. The main objective is to show that automatic labeling of images with semantic labels can improve image retrieval results. |
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Publisher |
Springer Berlin Heidelberg |
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Editor |
Angel Sappa; Jordi Vitria |
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ISSN |
1868-4394 |
ISBN |
978-3-642-35931-6 |
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Notes |
CIC; 605.203; 600.048 |
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no |
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Call Number |
Admin @ si @ WKC2013 |
Serial |
2284 |
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Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg |
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Title |
Coloring Action Recognition in Still Images |
Type |
Journal Article |
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Year |
2013 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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Volume |
105 |
Issue |
3 |
Pages |
205-221 |
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Abstract |
In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color–shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification. |
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Springer US |
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ISSN |
0920-5691 |
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Notes |
CIC; ADAS; 600.057; 600.048 |
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no |
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Call Number |
Admin @ si @ KRW2013 |
Serial |
2285 |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames |
Type |
Conference Article |
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Year |
2013 |
Publication |
35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
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Pages |
7350 - 7354 |
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Abstract |
In this paper we present our image preprocessing methods as a key part of our automatic polyp localization scheme. These methods are used to assess the impact of different endoluminal scene elements when characterizing polyps. More precisely we tackle the influence of specular highlights, blood vessels and black mask surrounding the scene. Experimental results prove that the appropriate handling of these elements leads to a great improvement in polyp localization results. |
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Osaka; Japan; July 2013 |
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ISSN |
1557-170X |
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Area |
800 |
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Conference |
EMBC |
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Notes |
MV; 600.047; 600.060;SIAI |
Approved |
no |
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Call Number |
Admin @ si @ BSV2013 |
Serial |
2286 |
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