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Author Marc Sunset Perez; Marc Comino Trinidad; Dimosthenis Karatzas; Antonio Chica Calaf; Pere Pau Vazquez Alcocer edit  url
openurl 
  Title Development of general‐purpose projection‐based augmented reality systems Type Journal
  Year (down) 2016 Publication IADIs international journal on computer science and information systems Abbreviated Journal IADIs  
  Volume 11 Issue 2 Pages 1-18  
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  Abstract Despite the large amount of methods and applications of augmented reality, there is little homogenizatio n on the software platforms that support them. An exception may be the low level control software that is provided by some high profile vendors such as Qualcomm and Metaio. However, these provide fine grain modules for e.g. element tracking. We are more co ncerned on the application framework, that includes the control of the devices working together for the development of the AR experience. In this paper we describe the development of a software framework for AR setups. We concentrate on the modular design of the framework, but also on some hard problems such as the calibration stage, crucial for projection – based AR. The developed framework is suitable and has been tested in AR applications using camera – projector pairs, for both fixed and nomadic setups  
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  Notes DAG; 600.084 Approved no  
  Call Number Admin @ si @ SCK2016 Serial 2890  
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Author Alicia Fornes; Josep Llados; Oriol Ramos Terrades; Marçal Rusiñol edit   pdf
openurl 
  Title La Visió per Computador com a Eina per a la Interpretació Automàtica de Fonts Documentals Type Journal
  Year (down) 2016 Publication Lligall, Revista Catalana d'Arxivística Abbreviated Journal  
  Volume 39 Issue Pages 20-46  
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  Notes DAG; 600.097 Approved no  
  Call Number Admin @ si @ FLR2016 Serial 2897  
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Author Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades edit   pdf
url  openurl
  Title Sparse representation over learned dictionary for symbol recognition Type Journal Article
  Year (down) 2016 Publication Signal Processing Abbreviated Journal SP  
  Volume 125 Issue Pages 36-47  
  Keywords Symbol Recognition; Sparse Representation; Learned Dictionary; Shape Context; Interest Points  
  Abstract In this paper we propose an original sparse vector model for symbol retrieval task. More speci cally, we apply the K-SVD algorithm for learning a visual dictionary based on symbol descriptors locally computed around interest points. Results on benchmark datasets show that the obtained sparse representation is competitive related to state-of-the-art methods. Moreover, our sparse representation is invariant to rotation and scale transforms and also robust to degraded images and distorted symbols. Thereby, the learned visual dictionary is able to represent instances of unseen classes of symbols.  
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  Notes DAG; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ DTR2016 Serial 2946  
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Author Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Benedi edit   pdf
openurl 
  Title Structure Detection and Segmentation of Documents Using 2D Stochastic Context-Free Grammars Type Journal Article
  Year (down) 2015 Publication Neurocomputing Abbreviated Journal NEUCOM  
  Volume 150 Issue A Pages 147-154  
  Keywords document image analysis; stochastic context-free grammars; text classi cation features  
  Abstract In this paper we de ne a bidimensional extension of Stochastic Context-Free Grammars for structure detection and segmentation of images of documents.
Two sets of text classi cation features are used to perform an initial classi cation of each zone of the page. Then, the document segmentation is obtained as the most likely hypothesis according to a stochastic grammar. We used a dataset of historical marriage license books to validate this approach. We also tested several inference algorithms for Probabilistic Graphical Models
and the results showed that the proposed grammatical model outperformed
the other methods. Furthermore, grammars also provide the document structure
along with its segmentation.
 
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  Notes DAG; 601.158; 600.077; 600.061 Approved no  
  Call Number Admin @ si @ ACS2015 Serial 2531  
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Author Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados edit  doi
openurl 
  Title Efficient segmentation-free keyword spotting in historical document collections Type Journal Article
  Year (down) 2015 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 48 Issue 2 Pages 545–555  
  Keywords Historical documents; Keyword spotting; Segmentation-free; Dense SIFT features; Latent semantic analysis; Product quantization  
  Abstract In this paper we present an efficient segmentation-free word spotting method, applied in the context of historical document collections, that follows the query-by-example paradigm. We use a patch-based framework where local patches are described by a bag-of-visual-words model powered by SIFT descriptors. By projecting the patch descriptors to a topic space with the latent semantic analysis technique and compressing the descriptors with the product quantization method, we are able to efficiently index the document information both in terms of memory and time. The proposed method is evaluated using four different collections of historical documents achieving good performances on both handwritten and typewritten scenarios. The yielded performances outperform the recent state-of-the-art keyword spotting approaches.  
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  Notes DAG; ADAS; 600.076; 600.077; 600.061; 601.223; 602.006; 600.055 Approved no  
  Call Number Admin @ si @ RAT2015a Serial 2544  
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