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Author |
Jon Almazan; Ernest Valveny; Alicia Fornes |
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Title |
Deforming the Blurred Shape Model for Shape Description and Recognition |
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Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
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6669 |
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1-8 |
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Abstract |
This paper presents a new model for the description and recognition of distorted shapes, where the image is represented by a pixel density distribution based on the Blurred Shape Model combined with a non-linear image deformation model. This leads to an adaptive structure able to capture elastic deformations in shapes. This method has been evaluated using thee different datasets where deformations are present, showing the robustness and good performance of the new model. Moreover, we show that incorporating deformation and flexibility, the new model outperforms the BSM approach when classifying shapes with high variability of appearance. |
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Las Palmas de Gran Canaria. Spain |
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Springer-Verlag |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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IbPRIA |
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DAG; |
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no |
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Call Number |
Admin @ si @ AVF2011 |
Serial |
1732 |
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Author |
Lluis Pere de las Heras; Gemma Sanchez |
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Title |
And-Or Graph Grammar for Architectural Floorplan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
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Pages |
17-24 |
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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. |
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Las Palmas de Gran Canaria. Spain |
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978-3-642-21256-7 |
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IbPRIA |
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DAG |
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no |
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Call Number |
Admin @ si @ HeS2011 |
Serial |
1736 |
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Author |
Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados |
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Title |
Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval |
Type |
Conference Article |
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Year |
2011 |
Publication |
33rd European Conference on Information Retrieval |
Abbreviated Journal |
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Volume |
6611 |
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Pages |
314-325 |
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Abstract |
In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset. |
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Dublin, Ireland |
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Springer |
Place of Publication |
Berlin |
Editor |
P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch |
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978-3-642-20160-8 |
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ECIR |
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Notes |
DAG; RV;ADAS |
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no |
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Call Number |
Admin @ si @ RAK2011 |
Serial |
1737 |
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Author |
Anjan Dutta; Josep Llados; Umapada Pal |
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Title |
A Bag-of-Paths Based Serialized Subgraph Matching for Symbol Spotting in Line Drawings |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
620-627 |
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Abstract |
In this paper we propose an error tolerant subgraph matching algorithm based on bag-of-paths for solving the problem of symbol spotting in line drawings. Bag-of-paths is a factorized representation of graphs where the factorization is done by considering all the acyclic paths between each pair of connected nodes. Similar paths within the whole collection of documents are clustered and organized in a lookup table for efficient indexing. The lookup table contains the index key of each cluster and the corresponding list of locations as a single entry. The mean path of each of the clusters serves as the index key for each table entry. The spotting method is then formulated by a spatial voting scheme to the list of locations of the paths that are decided in terms of search of similar paths that compose the query symbol. Efficient indexing of common substructures helps to reduce the computational burden of usual graph based methods. The proposed method can also be seen as a way to serialize graphs which allows to reduce the complexity of the subgraph isomorphism. We have encoded the paths in terms of both attributed strings and turning functions, and presented a comparative results between them within the symbol spotting framework. Experimentations for matching different shape silhouettes are also reported and the method has been proved to work in noisy environment also. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
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IbPRIA |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ DLP2011a |
Serial |
1738 |
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Author |
David Fernandez; Josep Llados; Alicia Fornes |
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Title |
Handwritten Word Spotting in Old Manuscript Images Using a Pseudo-Structural Descriptor Organized in a Hash Structure |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
628-635 |
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Abstract |
There are lots of historical handwritten documents with information that can be used for several studies and projects. The Document Image Analysis and Recognition community is interested in preserving these documents and extracting all the valuable information from them. Handwritten word-spotting is the pattern classification task which consists in detecting handwriting word images. In this work, we have used a query-by-example formalism: we have matched an input image with one or multiple images from handwritten documents to determine the distance that might indicate a correspondence. We have developed an approach based in characteristic Loci Features stored in a hash structure. Document images of the marriage licences of the Cathedral of Barcelona are used as the benchmarking database. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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978-3-642-21256-7 |
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IbPRIA |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ FLF2011 |
Serial |
1742 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Dimensionality Reduction for Graph of Words Embedding |
Type |
Conference Article |
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Year |
2011 |
Publication |
8th IAPR-TC-15 International Workshop. Graph-Based Representations in Pattern Recognition |
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Volume |
6658 |
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Pages |
22-31 |
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Abstract |
The Graph of Words Embedding consists in mapping every graph of a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. While it shows good properties in classification problems, it suffers from high dimensionality and sparsity. These two issues are addressed in this article. Two well-known techniques for dimensionality reduction, kernel principal component analysis (kPCA) and independent component analysis (ICA), are applied to the embedded graphs. We discuss their performance compared to the classification of the original vectors on three different public databases of graphs. |
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Address |
Münster, Germany |
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Editor |
Xiaoyi Jiang; Miquel Ferrer; Andrea Torsello |
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LNCS |
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978-3-642-20843-0 |
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GbRPR |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ GVB2011a |
Serial |
1743 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Vocabulary Selection for Graph of Words Embedding |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
216-223 |
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Abstract |
The Graph of Words Embedding consists in mapping every graph in a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. It has been shown to perform well for graphs with discrete label alphabets. In this paper we extend the methodology to graphs with n-dimensional continuous attributes by selecting node representatives. We propose three different discretization procedures for the attribute space and experimentally evaluate the dependence on both the selector and the number of node representatives. In the context of graph classification, the experimental results reveal that on two out of three public databases the proposed extension achieves superior performance over a standard reference system. |
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Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer |
Place of Publication |
Berlin |
Editor |
Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
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LNCS |
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978-3-642-21256-7 |
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IbPRIA |
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DAG |
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no |
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Call Number |
Admin @ si @ GVB2011b |
Serial |
1744 |
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Author |
Jaume Gibert; Ernest Valveny; Oriol Ramos Terrades; Horst Bunke |
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Title |
Multiple Classifiers for Graph of Words Embedding |
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Conference Article |
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Year |
2011 |
Publication |
10th International Conference on Multiple Classifier Systems |
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Volume |
6713 |
Issue |
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Pages |
36-45 |
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Abstract |
During the last years, there has been an increasing interest in applying the multiple classifier framework to the domain of structural pattern recognition. Constructing base classifiers when the input patterns are graph based representations is not an easy problem. In this work, we make use of the graph embedding methodology in order to construct different feature vector representations for graphs. The graph of words embedding assigns a feature vector to every graph by counting unary and binary relations between node representatives and combining these pieces of information into a single vector. Selecting different node representatives leads to different vectorial representations and therefore to different base classifiers that can be combined. We experimentally show how this methodology significantly improves the classification of graphs with respect to single base classifiers. |
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Address |
Napoles, Italy |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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LNCS |
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978-3-642-21556-8 |
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MCS |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @GVR2011 |
Serial |
1745 |
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Author |
Jon Almazan; Alicia Fornes; Ernest Valveny |
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Title |
A Non-Rigid Feature Extraction Method for Shape Recognition |
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Conference Article |
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Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
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Pages |
987-991 |
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Abstract |
This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost. |
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Beijing; China; September 2011 |
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978-0-7695-4520-2 |
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ICDAR |
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DAG |
Approved |
no |
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Call Number |
Admin @ si @ AFV2011 |
Serial |
1763 |
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Author |
Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner |
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Title |
Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation |
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Journal |
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Year |
2011 |
Publication |
e-Perimetron |
Abbreviated Journal |
ePER |
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Volume |
6 |
Issue |
4 |
Pages |
219-229 |
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Abstract |
By means of computer vision algorithms scanned images of maps are processed in order to extract relevant geographic information from printed coordinate pairs. The meaningful information is then transformed into georeferencing information for each single map sheet, and the complete set is compiled to produce a graphical index sheet for the map series along with relevant metadata. The whole process is fully automated and trained to attain maximum effectivity and throughput. |
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DAG |
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Call Number |
Admin @ si @ RRL2011a |
Serial |
1765 |
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