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Records |
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Author |
Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Combining structural and statistical strategies for unsupervised wall detection in floor plans |
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Conference Article |
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Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
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This paper presents an evolution of the first unsupervised wall segmentation method in floor plans, that was presented by the authors in [1]. This first approach, contrarily to the existing ones, is able to segment walls independently to their notation and without the need of any pre-annotated data
to learn their visual appearance. Despite the good performance of the first approach, some specific cases, such as curved shaped walls, were not correctly segmented since they do not agree the strict structural assumptions that guide the whole methodology in order to be able to learn, in an unsupervised way, the structure of a wall. In this paper, we refine this strategy by dividing the
process in two steps. In a first step, potential wall segments are extracted unsupervisedly using a modification of [1], by restricting even more the areas considered as walls in a first moment. In a second step, these segments are used to learn and spot lost instances based on a modified version of [2], also presented by the authors. The presented combined method have been tested on
4 datasets with different notations and compared with the stateof-the-art applyed on the same datasets. The results show its adaptability to different wall notations and shapes, significantly outperforming the original approach. |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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DAG; 600.045 |
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Admin @ si @ HVS2013a |
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2321 |
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Author |
Lluis Gomez |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Perceptual Organization for Text Extraction in Natural Scenes |
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Report |
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2012 |
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CVC Technical Report |
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173 |
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Bellaterra |
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Master's thesis |
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Admin @ si @ Gom2012 |
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2309 |
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Author |
Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Apostolos Antonacopoulos; Josep Llados |
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Title |
An interactive appearance-based document retrieval system for historical newspapers |
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Conference Article |
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2013 |
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Proceedings of the International Conference on Computer Vision Theory and Applications |
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84-87 |
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In this paper we present a retrieval-based application aimed at assisting a user to semi-automatically segment an incoming flow of historical newspaper images by automatically detecting a particular type of pages based on their appearance. A visual descriptor is used to assess page similarity while a relevance feedback process allow refining the results iteratively. The application is tested on a large dataset of digitised historic newspapers. |
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Barcelona; February 2013 |
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VISAPP |
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DAG; 600.056; 600.045; 605.203 |
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Admin @ si @ GRK2013a |
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2290 |
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Author |
Albert Gordo |
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Title |
A Cyclic Page Layout Descriptor for Document Classification & Retrieval |
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2009 |
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CVC Technical Report |
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128 |
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Computer Vision Center |
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Master's thesis |
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Bellaterra, Barcelona |
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CIC;DAG |
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Admin @ si @ Gor2009 |
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2387 |
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Author |
Albert Gordo |
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Title |
Document Image Representation, Classification and Retrieval in Large-Scale Domains |
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2013 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Despite the “paperless office” ideal that started in the decade of the seventies, businesses still strive against an increasing amount of paper documentation. Companies still receive huge amounts of paper documentation that need to be analyzed and processed, mostly in a manual way. A solution for this task consists in, first, automatically scanning the incoming documents. Then, document images can be analyzed and information can be extracted from the data. Documents can also be automatically dispatched to the appropriate workflows, used to retrieve similar documents in the dataset to transfer information, etc.
Due to the nature of this “digital mailroom”, we need document representation methods to be general, i.e., able to cope with very different types of documents. We need the methods to be sound, i.e., able to cope with unexpected types of documents, noise, etc. And, we need to methods to be scalable, i.e., able to cope with thousands or millions of documents that need to be processed, stored, and consulted. Unfortunately, current techniques of document representation, classification and retrieval are not apt for this digital mailroom framework, since they do not fulfill some or all of these requirements.
Through this thesis we focus on the problem of document representation aimed at classification and retrieval tasks under this digital mailroom framework. We first propose a novel document representation based on runlength histograms, and extend it to cope with more complex documents such as multiple-page documents, or documents that contain more sources of information such as extracted OCR text. Then we focus on the scalability requirements and propose a novel binarization method which we dubbed PCAE, as well as two general asymmetric distances between binary embeddings that can significantly improve the retrieval results at a minimal extra computational cost. Finally, we note the importance of supervised learning when performing large-scale retrieval, and study several approaches that can significantly boost the results at no extra cost at query time. |
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Barcelona |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Ernest Valveny;Florent Perronnin |
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DAG |
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Admin @ si @ Gor2013 |
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2277 |
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Author |
Jean-Marc Ogier; Wenyin Liu; Josep Llados (eds) |
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Title |
Graphics Recognition: Achievements, Challenges, and Evolution |
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Book Whole |
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2010 |
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8th International Workshop GREC 2009. |
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6020 |
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La Rochelle |
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Springer Link |
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Jean-Marc Ogier; Wenyin Liu; Josep Llados |
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Lecture Notes in Computer Science |
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978-3-642-13727-3 |
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GREC |
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Admin @ si @ OLL2010 |
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1976 |
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Author |
Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
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Title |
Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation |
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Conference Article |
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2011 |
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In Proceedings of the Sixth International Workshop on Digital Technologies in Cartographic Heritage |
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CartoHerit |
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Admin @ si @ RRL2011b |
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1978 |
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Author |
Dimosthenis Karatzas;Ch. Lioutas |
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Title |
Software Package Development for Electron Diffraction Image Analysis |
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1998 |
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Proceedings of the XIV Solid State Physics National Conference |
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Ioannina, Greece |
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IAM @ iam @ KaL1998 |
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2045 |
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Author |
Volkmar Frinken; Francisco Zamora; Salvador España; Maria Jose Castro; Andreas Fischer; Horst Bunke |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Long-Short Term Memory Neural Networks Language Modeling for Handwriting Recognition |
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Conference Article |
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2012 |
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21st International Conference on Pattern Recognition |
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701-704 |
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Unconstrained handwritten text recognition systems maximize the combination of two separate probability scores. The first one is the observation probability that indicates how well the returned word sequence matches the input image. The second score is the probability that reflects how likely a word sequence is according to a language model. Current state-of-the-art recognition systems use statistical language models in form of bigram word probabilities. This paper proposes to model the target language by means of a recurrent neural network with long-short term memory cells. Because the network is recurrent, the considered context is not limited to a fixed size especially as the memory cells are designed to deal with long-term dependencies. In a set of experiments conducted on the IAM off-line database we show the superiority of the proposed language model over statistical n-gram models. |
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Tsukuba Science City, Japan |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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Admin @ si @ FZE2012 |
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2052 |
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Author |
Marçal Rusiñol; Dimosthenis Karatzas; Andrew Bagdanov; Josep Llados |
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Title |
Multipage Document Retrieval by Textual and Visual Representations |
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Conference Article |
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2012 |
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21st International Conference on Pattern Recognition |
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521-524 |
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In this paper we present a multipage administrative document image retrieval system based on textual and visual representations of document pages. Individual pages are represented by textual or visual information using a bag-of-words framework. Different fusion strategies are evaluated which allow the system to perform multipage document retrieval on the basis of a single page retrieval system. Results are reported on a large dataset of document images sampled from a banking workflow. |
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Tsukuba Science City, Japan |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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Admin @ si @ RKB2012 |
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2053 |
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