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Author |
Joan Mas; B. Lamiroy; Gemma Sanchez; Josep Llados |
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Title |
Automatic Adjacency Grammar Generation from User Drawn Sketches |
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Miscellaneous |
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2006 |
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18th International Conference on Pattern Recognition (ICPR´06), 2: 1026–1029 |
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Hong Kong |
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DAG @ dag @ MLS2006a |
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709 |
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Joan Mas; B. Lamiroy; Gemma Sanchez; Josep Llados |
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Title |
Automatic Learning of Symbol Descriptions Avoiding Topological Ambiguities |
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Miscellaneous |
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2006 |
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3rd Eurographics Workshop on Sketch Based Interfaces and Modeling (SBIM´06), 27–34 |
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Vienna (Austria) |
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DAG @ dag @ MLS2006b |
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710 |
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Joan Mas; Josep Llados; Gemma Sanchez; J.A. Jorge |
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Title |
A syntactic approach based on distortion-tolerant Adjacency Grammars and a spatial-directed parser to interpret sketched diagrams |
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Journal Article |
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2010 |
Publication |
Pattern Recognition |
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PR |
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43 |
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12 |
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4148–4164 |
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Syntactic Pattern Recognition; Symbol recognition; Diagram understanding; Sketched diagrams; Adjacency Grammars; Incremental parsing; Spatial directed parsing |
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This paper presents a syntactic approach based on Adjacency Grammars (AG) for sketch diagram modeling and understanding. Diagrams are a combination of graphical symbols arranged according to a set of spatial rules defined by a visual language. AG describe visual shapes by productions defined in terms of terminal and non-terminal symbols (graphical primitives and subshapes), and a set functions describing the spatial arrangements between symbols. Our approach to sketch diagram understanding provides three main contributions. First, since AG are linear grammars, there is a need to define shapes and relations inherently bidimensional using a sequential formalism. Second, our parsing approach uses an indexing structure based on a spatial tessellation. This serves to reduce the search space when finding candidates to produce a valid reduction. This allows order-free parsing of 2D visual sentences while keeping combinatorial explosion in check. Third, working with sketches requires a distortion model to cope with the natural variations of hand drawn strokes. To this end we extended the basic grammar with a distortion measure modeled on the allowable variation on spatial constraints associated with grammar productions. Finally, the paper reports on an experimental framework an interactive system for sketch analysis. User tests performed on two real scenarios show that our approach is usable in interactive settings. |
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Elsevier |
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DAG @ dag @ MLS2010 |
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1336 |
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Sebastien Mace; Herve Locteau; Ernest Valveny; Salvatore Tabbone |
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Title |
A system to detect rooms in architectural floor plan images |
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2010 |
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9th IAPR International Workshop on Document Analysis Systems |
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167–174 |
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In this article, a system to detect rooms in architectural floor plan images is described. We first present a primitive extraction algorithm for line detection. It is based on an original coupling of classical Hough transform with image vectorization in order to perform robust and efficient line detection. We show how the lines that satisfy some graphical arrangements are combined into walls. We also present the way we detect some door hypothesis thanks to the extraction of arcs. Walls and door hypothesis are then used by our room segmentation strategy; it consists in recursively decomposing the image until getting nearly convex regions. The notion of convexity is difficult to quantify, and the selection of separation lines between regions can also be rough. We take advantage of knowledge associated to architectural floor plans in order to obtain mostly rectangular rooms. Qualitative and quantitative evaluations performed on a corpus of real documents show promising results. |
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Boston; USA |
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978-1-60558-773-8 |
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DAG @ dag @ MLV2010 |
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1437 |
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Author |
Joan Mas; Jose Antonio Rodriguez; Dimosthenis Karatzas; Gemma Sanchez; Josep Llados |
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Title |
HistoSketch: A Semi-Automatic Annotation Tool for Archival Documents |
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Conference Article |
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2008 |
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Proceedings of the 8th International Workshop on Document Analysis Systems, |
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517–524 |
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Nara (Japan) |
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DAG @ dag @ MRK2008a |
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1061 |
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Author |
Joan Mas; Gemma Sanchez; Josep Llados |
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Title |
An Adjacency Grammar to Recognize Symbols and Gestures in a Digital Pen Framework |
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2005 |
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Pattern Recognition and Image Analysis (IbPRIA 2005), LNCS 3523: 115–122 |
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Estoril (Portugal) |
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DAG @ dag @ MSL2005a |
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558 |
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Joan Mas; Gemma Sanchez; Josep Llados |
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An Incremental Parser to Recognize Diagram Symbols and Gestures represented by Adjacency Grammars |
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Miscellaneous |
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2005 |
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Sixth IAPR International Workshop on Graphics Recognition (GREC 2005), 229–237 |
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Hong Kong (China) |
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DAG @ dag @ MSL2005b |
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611 |
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Joan Mas; Gemma Sanchez; Josep Llados |
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An Incremental Parser to Recognize Diagram Symbols and Gestures represented by Adjacency Grammars |
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2006 |
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Graphics Recognition: Ten Years Review and Future Perspectives, W. Liu, J. Llados (Eds.), LNCS 3926: 252–263 |
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DAG @ dag @ MSL2006a |
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711 |
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Joan Mas; Gemma Sanchez; Josep Llados; B. Lamiroy |
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Title |
An Incremental On-line Parsing Algorithm for Recognizing Sketching Diagrams |
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Conference Article |
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2007 |
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9th IEEE International Conference on Document Analysis and Recognition |
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1 |
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452–456 |
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Curitiba (Brazil) |
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ICDAR |
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DAG |
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DAG @ dag @ MSL2007a |
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847 |
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Joan Mas; Gemma Sanchez; Josep Llados |
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Title |
SSP: Sketching slide Presentations, a Syntactic Approach |
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Conference Article |
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2009 |
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8th IAPR International Workshop on Graphics Recognition |
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The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide. |
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La Rochelle; France; July 2009 |
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GREC |
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DAG @ dag @ MSL2009a |
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1441 |
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Farshad Nourbakhsh; Dimosthenis Karatzas; Ernest Valveny |
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A polar-based logo representation based on topological and colour features |
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2010 |
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9th IAPR International Workshop on Document Analysis Systems |
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341–348 |
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In this paper, we propose a novel rotation and scale invariant method for colour logo retrieval and classification, which involves performing a simple colour segmentation and subsequently describing each of the resultant colour components based on a set of topological and colour features. A polar representation is used to represent the logo and the subsequent logo matching is based on Cyclic Dynamic Time Warping (CDTW). We also show how combining information about the global distribution of the logo components and their local neighbourhood using the Delaunay triangulation allows to improve the results. All experiments are performed on a dataset of 2500 instances of 100 colour logo images in different rotations and scales. |
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Boston; USA; |
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978-1-60558-773-8 |
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DAG @ dag @ NKV2010 |
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1436 |
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X. Orriols; Andrew Willis; X. Binefa; David B. Cooper |
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Bayesian estimation of axial symmetries from partial data, a generative model approach |
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2000 |
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CVC Technical Report #49 |
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CVC (UAB) |
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DAG @ dag @ OWB2000 |
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536 |
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Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva |
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Recursive Coarse-to-Fine Localization for fast Object Recognition |
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2010 |
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11th European Conference on Computer Vision |
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6313 |
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II |
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280–293 |
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Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors and corresponding thresholds to learn. Furthermore, they do not use any prior knowledge about the scene structure to decide where to focus the search. To handle these problems, we propose a new way to scan an image, where we couple a recursive coarse-to-fine refinement together with spatial constraints of the object location. For doing that we split an image into a set of uniformly distributed neighborhood regions, and for each of these we apply a local greedy search over feature resolutions. The neighborhood is defined as a scanning region that only one object can occupy. Therefore the best hypothesis is obtained as the location with maximum score and no thresholds are needed. We present an implementation of our method using a pyramid of HOG features and we evaluate it on two standard databases, VOC2007 and INRIA dataset. Results show that the Recursive Coarse-to-Fine Localization (RCFL) achieves a 12x speed-up compared to standard sliding windows. Compared with a cascade of multiple resolutions approach our method has slightly better performance in speed and Average-Precision. Furthermore, in contrast to cascading approach, the speed-up is independent of image conditions, the number of detected objects and clutter. |
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Crete (Greece) |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-15566-6 |
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ECCV |
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DAG @ dag @ PGB2010 |
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1438 |
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Umapada Pal; Partha Pratim Roy; N. Tripathya; Josep Llados |
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Multi-oriented Bangla and Devnagari text recognition |
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2010 |
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Pattern Recognition |
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43 |
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12 |
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4124–4136 |
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There are printed complex documents where text lines of a single page may have different orientations or the text lines may be curved in shape. As a result, it is difficult to detect the skew of such documents and hence character segmentation and recognition of such documents are a complex task. In this paper, using background and foreground information we propose a novel scheme towards the recognition of Indian complex documents of Bangla and Devnagari script. In Bangla and Devnagari documents usually characters in a word touch and they form cavity regions. To take care of these cavity regions, background information of such documents is used. Convex hull and water reservoir principle have been applied for this purpose. Here, at first, the characters are segmented from the documents using the background information of the text. Next, individual characters are recognized using rotation invariant features obtained from the foreground part of the characters.
For character segmentation, at first, writing mode of a touching component (word) is detected using water reservoir principle based features. Next, depending on writing mode and the reservoir base-region of the touching component, a set of candidate envelope points is then selected from the contour points of the component. Based on these candidate points, the touching component is finally segmented into individual characters. For recognition of multi-sized/multi-oriented characters the features are computed from different angular information obtained from the external and internal contour pixels of the characters. These angular information are computed in such a way that they do not depend on the size and rotation of the characters. Circular and convex hull rings have been used to divide a character into smaller zones to get zone-wise features for higher recognition results. We combine circular and convex hull features to improve the results and these features are fed to support vector machines (SVM) for recognition. From our experiment we obtained recognition results of 99.18% (98.86%) accuracy when tested on 7515 (7874) Devnagari (Bangla) characters. |
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Elsevier |
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DAG @ dag @ PRT2010 |
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1337 |
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Oriol Ramos Terrades |
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Descripcio i classificacio de simbols tecnics usant la transformada de crestetes |
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2003 |
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CVC Technical Report #74 |
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DAG |
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no |
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Call Number |
DAG @ dag @ Ram2003 |
Serial |
517 |
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