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Author Lluis Pere de las Heras edit  isbn
openurl 
  Title Relational Models for Visual Understanding of Graphical Documents. Application to Architectural Drawings. Type Book Whole
  Year 2014 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Graphical documents express complex concepts using a visual language. This language consists of a vocabulary (symbols) and a syntax (structural relations between symbols) that articulate a semantic meaning in a certain context. Therefore, the automatic interpretation by computers of these sort of documents entails three main steps: the detection of the symbols, the extraction of the structural relations between these symbols, and the modeling of the knowledge that permits the extraction of the semantics. Di erent domains in graphical documents include: architectural and engineering drawings, maps, owcharts, etc.
Graphics Recognition in particular and Document Image Analysis in general are
born from the industrial need of interpreting a massive amount of digitalized documents after the emergence of the scanner. Although many years have passed, the graphical document understanding problem still seems to be far from being solved. The main reason is that the vast majority of the systems in the literature focus on very speci c problems, where the domain of the document dictates the implementation of the interpretation. As a result, it is dicult to reuse these strategies on di erent data and on di erent contexts, hindering thus the natural progress in the eld.
In this thesis, we face the graphical document understanding problem by proposing several relational models at di erent levels that are designed from a generic perspective. Firstly, we introduce three di erent strategies for the detection of symbols. The fi rst method tackles the problem structurally, wherein general knowledge of the domain guides the detection. The second is a statistical method that learns the graphical appearance of the symbols and easily adapts to the big variability of the problem. The third method is a combination of the previous two methods that inherits their respective strengths, i.e. copes the big variability and does not need annotated data. Secondly, we present two relational strategies that tackle the problem of the visual context extraction. The fi rst one is a full bottom up method that heuristically searches in a graph representation the contextual relations between symbols. Contrarily, the second is syntactic method that models probabilistically the structure of the documents. It automatically learns the model, which guides the inference algorithm to encounter the best structural representation for a given input. Finally, we construct a knowledge-based model consisting of an ontological de nition of the domain and real data. This model permits to perform contextual reasoning and to detect semantic inconsistencies within the data. We evaluate the suitability of the proposed contributions in the framework of floor plan interpretation. Since there is no standard in the modeling of these documents there exists an enormous notation variability from plan to plan in terms of vocabulary and syntax. Therefore, floor plan interpretation is a relevant task in the graphical document understanding problem. It is also worth to mention that we make freely available all the resources used in this thesis {the data, the tool used to generate the data, and the evaluation scripts{ with the aim of fostering research in the graphical document understanding task.
 
  Address  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Gemma Sanchez  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-940902-8-8 Medium  
  Area Expedition Conference  
  Notes DAG; 600.077 Approved no  
  Call Number (up) Admin @ si @ Her2014 Serial 2574  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; Gemma Sanchez edit  doi
isbn  openurl
  Title And-Or Graph Grammar for Architectural Floorplan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model Type Conference Article
  Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 6669 Issue Pages 17-24  
  Keywords  
  Abstract This paper presents a syntactic model for architectural floor plan interpretation. A stochastic image grammar over an And-Or graph is inferred to represent the hierarchical, structural and semantic relations between elements of all possible floor plans. This grammar is augmented with three different probabilistic models, learnt from a training set, to account the frequency of that relations. Then, a Bottom-Up/Top-Down parser with a pruning strategy has been used for floor plan recognition. For a given input, the parser generates the most probable parse graph for that document. This graph not only contains the structural and semantic relations of its elements, but also its hierarchical composition, that allows to interpret the floor plan at different levels of abstraction.  
  Address Las Palmas de Gran Canaria. Spain  
  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 978-3-642-21256-7 Medium  
  Area Expedition Conference IbPRIA  
  Notes DAG Approved no  
  Call Number (up) Admin @ si @ HeS2011 Serial 1736  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez;Josep Llados edit   pdf
openurl 
  Title Perceptual retrieval of architectural floor plans Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract This paper proposes a runlength histogram signature as a percetual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query,
similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Preliminary results show the interest of the proposed approach and opens a challenging research line in graphics recognition.
 
  Address Bethlehem; PA; USA; August 2013  
  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 GREC  
  Notes DAG; 600.045; 600.056; 600.061 Approved no  
  Call Number (up) Admin @ si @ HFF2013a Serial 2320  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados edit  openurl
  Title Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Bethlehem; PA; USA; August 2013  
  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 GREC  
  Notes DAG; 600.045; 600.061; 600.056 Approved no  
  Call Number (up) Admin @ si @ HFF2013b Serial 2695  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados edit  doi
isbn  openurl
  Title Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 135-146  
  Keywords Graphics recognition; Graphics retrieval; Image classification  
  Abstract This paper proposes a runlength histogram signature as a perceptual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query, similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Additional retrieval results on sketched building’s facades are reported qualitatively in this paper. Its good description and its adaptability to two different sketch drawings despite its simplicity shows the interest of the proposed approach and opens a challenging research line in graphics recognition.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; ADAS; 600.045; 600.056; 600.061; 600.076; 600.077 Approved no  
  Call Number (up) Admin @ si @ HFF2014 Serial 2536  
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Author Lluis Pere de las Heras; David Fernandez; Ernest Valveny; Josep Llados; Gemma Sanchez edit   pdf
doi  openurl
  Title Unsupervised wall detector in architectural floor plan Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1245-1249  
  Keywords  
  Abstract Wall detection in floor plans is a crucial step in a complete floor plan recognition system. Walls define the main structure of buildings and convey essential information for the detection of other structural elements. Nevertheless, wall segmentation is a difficult task, mainly because of the lack of a standard graphical notation. The existing approaches are restricted to small group of similar notations or require the existence of pre-annotated corpus of input images to learn each new notation. In this paper we present an automatic wall segmentation system, with the ability to handle completely different notations without the need of any annotated dataset. It only takes advantage of the general knowledge that walls are a repetitive element, naturally distributed within the plan and commonly modeled by straight parallel lines. The method has been tested on four datasets of real floor plans with different notations, and compared with the state-of-the-art. The results show its suitability for different graphical notations, achieving higher recall rates than the rest of the methods while keeping a high average precision.  
  Address Washington; USA; August 2013  
  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 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.061; 600.056; 600.045 Approved no  
  Call Number (up) Admin @ si @ HFV2013 Serial 2319  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny edit  url
doi  isbn
openurl 
  Title Wall Patch-Based Segmentation in Architectural Floorplans Type Conference Article
  Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1270-1274  
  Keywords  
  Abstract Segmentation of architectural floor plans is a challenging task, mainly because of the large variability in the notation between different plans. In general, traditional techniques, usually based on analyzing and grouping structural primitives obtained by vectorization, are only able to handle a reduced range of similar notations. In this paper we propose an alternative patch-based segmentation approach working at pixel level, without need of vectorization. The image is divided into a set of patches and a set of features is extracted for every patch. Then, each patch is assigned to a visual word of a previously learned vocabulary and given a probability of belonging to each class of objects. Finally, a post-process assigns the final label for every pixel. This approach has been applied to the detection of walls on two datasets of architectural floor plans with different notations, achieving high accuracy rates.  
  Address Beiging, China  
  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 1520-5363 ISBN 978-0-7695-4520-2 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number (up) Admin @ si @ HMS2011a Serial 1792  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny edit  openurl
  Title Descriptor-based Svm Wall Detector Type Conference Article
  Year 2011 Publication 9th International Workshop on Graphic Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Architectural floorplans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. In this paper we describe an evolution of this new approach in two directions: firstly we evaluate different features to obtain the description of every patch. Secondly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These modifications of the method have been tested for wall detection on two datasets of architectural floorplans with different notations and compared with the results obtained with the original approach.  
  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 Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number (up) Admin @ si @ HMS2011b Serial 1819  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny edit   pdf
doi  isbn
openurl 
  Title Notation-invariant patch-based wall detector in architectural floor plans Type Book Chapter
  Year 2013 Publication Graphics Recognition. New Trends and Challenges Abbreviated Journal  
  Volume 7423 Issue Pages 79--88  
  Keywords  
  Abstract Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-36823-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.045; 600.056; 605.203 Approved no  
  Call Number (up) Admin @ si @ HMS2013 Serial 2322  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; Oriol Ramos Terrades; Josep Llados; David Fernandez; Cristina Cañero edit  doi
openurl 
  Title Use case visual Bag-of-Words techniques for camera based identity document classification Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume Issue Pages 721 - 725  
  Keywords  
  Abstract Nowadays, automatic identity document recognition, including passport and driving license recognition, is at the core of many applications within the administrative and service sectors, such as police, hospitality, car renting, etc. In former years, the document information was manually extracted whereas today this data is recognized automatically from images obtained by flat-bed scanners. Yet, since these scanners tend to be expensive and voluminous, companies in the sector have recently turned their attention to cheaper, small and yet computationally powerful scanners: the mobile devices. The document identity recognition from mobile images enclose several new difficulties w.r.t traditional scanned images, such as the loss of a controlled background, perspective, blurring, etc. In this paper we present a real application for identity document classification of images taken from mobile devices. This classification process is of extreme importance since a prior knowledge of the document type and origin strongly facilitates the subsequent information extraction. The proposed method is based on a traditional Bagof-Words in which we have taken into consideration several key aspects to enhance recognition rate. The method performance has been studied on three datasets containing more than 2000 images from 129 different document classes.  
  Address Nancy; France; August 2015  
  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 ICDAR  
  Notes DAG; 600.077; 600.061; Approved no  
  Call Number (up) Admin @ si @ HRL2015a Serial 2726  
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