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Author |
Jordi Vitria; Joao Sanchez; Miguel Raposo; Mario Hernandez |
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Title |
Pattern Recognition and Image Analysis |
Type |
Book Whole |
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Year |
2011 |
Publication |
5th Iberian Conference Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
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Address |
Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer-Verlag |
Place of Publication |
Berlin |
Editor |
J. Vitrià; J. Sanchez; M. Raposo; M. Hernandez |
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ISBN |
978-3-642-2125 |
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Conference |
IbPRIA |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ VSR2011 |
Serial |
1730 |
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Permanent link to this record |
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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 |
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 |
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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Address |
Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer-Verlag |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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LNCS |
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IbPRIA |
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Notes |
DAG; |
Approved |
no |
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Call Number |
Admin @ si @ AVF2011 |
Serial |
1732 |
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Permanent link to this record |
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Author |
Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich |
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Title |
Perception Based Representations for Computational Colour |
Type |
Conference Article |
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Year |
2011 |
Publication |
3rd International Workshop on Computational Color Imaging |
Abbreviated Journal |
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Volume |
6626 |
Issue |
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Pages |
16-30 |
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Keywords |
colour perception, induction, naming, psychophysical data, saliency, segmentation |
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Abstract |
The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space. |
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Address |
Milan, Italy |
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Publisher |
Springer-Verlag |
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Editor |
Raimondo Schettini, Shoji Tominaga, Alain Trémeau |
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LNCS |
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Series Issue |
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Edition |
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ISBN |
978-3-642-20403-6 |
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Conference |
CCIW |
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Notes |
CIC |
Approved |
no |
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Call Number |
Admin @ si @ VMB2011 |
Serial |
1733 |
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Permanent link to this record |
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Author |
Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria; Petia Radeva |
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Title |
Interactive Labeling of WCE Images |
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 |
143-150 |
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Keywords |
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Abstract |
A high quality labeled training set is necessary for any supervised machine learning algorithm. Labeling of the data can be a very expensive process, specially while dealing with data of high variability and complexity. A good example of such data are the videos from Wireless Capsule Endoscopy. Building a representative WCE data set means many videos to be labeled by an expert. The problem that occurs is the data diversity, in the space of the features, from different WCE studies. That means that when new data arrives it is highly probable that it will not be represented in the training set, thus getting a high probability of performing an error when applying machine learning schemes. In this paper an interactive labeling scheme that allows reducing expert effort in the labeling process is presented. It is shown that the number of human interventions can be significantly reduced. The proposed system allows the annotation of informative/non-informative frames of the WCE video with less than 100 clicks |
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Address |
Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer |
Place of Publication |
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Editor |
Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
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Expedition |
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Conference |
IbPRIA |
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Notes |
MILAB;OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ DSM2011 |
Serial |
1734 |
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Permanent link to this record |
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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 |
Issue |
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Pages |
17-24 |
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Keywords |
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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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Address |
Las Palmas de Gran Canaria. Spain |
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Series Editor |
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Edition |
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ISSN |
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ISBN |
978-3-642-21256-7 |
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Expedition |
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Conference |
IbPRIA |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ HeS2011 |
Serial |
1736 |
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Permanent link to this record |
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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 |
Issue |
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Pages |
314-325 |
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Keywords |
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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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Address |
Dublin, Ireland |
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Publisher |
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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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
978-3-642-20160-8 |
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Expedition |
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Conference |
ECIR |
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Notes |
DAG; RV;ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RAK2011 |
Serial |
1737 |
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Permanent link to this record |
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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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Keywords |
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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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Corporate Author |
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Place of Publication |
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Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
978-3-642-21256-7 |
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Area |
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Expedition |
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Conference |
IbPRIA |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ FLF2011 |
Serial |
1742 |
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Permanent link to this record |
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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 |
Abbreviated Journal |
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Volume |
6658 |
Issue |
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Pages |
22-31 |
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Keywords |
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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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Place of Publication |
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Editor |
Xiaoyi Jiang; Miquel Ferrer; Andrea Torsello |
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LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
978-3-642-20843-0 |
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Expedition |
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Conference |
GbRPR |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ GVB2011a |
Serial |
1743 |
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Permanent link to this record |
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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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Keywords |
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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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Address |
Las Palmas de Gran Canaria. Spain |
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Corporate Author |
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Thesis |
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Publisher |
Springer |
Place of Publication |
Berlin |
Editor |
Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
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Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
978-3-642-21256-7 |
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Expedition |
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Conference |
IbPRIA |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ GVB2011b |
Serial |
1744 |
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Permanent link to this record |
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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 |
Type |
Conference Article |
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Year |
2011 |
Publication |
10th International Conference on Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
6713 |
Issue |
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Pages |
36-45 |
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Keywords |
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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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Series Editor |
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LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
978-3-642-21556-8 |
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Conference |
MCS |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @GVR2011 |
Serial |
1745 |
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Permanent link to this record |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Subtle Facial Expression Recognition in Still Images and Videos |
Type |
Book Chapter |
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Year |
2011 |
Publication |
Advances in Face Image Analysis: Techniques and Technologies |
Abbreviated Journal |
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Volume |
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Issue |
14 |
Pages |
259-277 |
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Abstract |
This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). |
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Publisher |
IGI-Global |
Place of Publication |
New York, USA |
Editor |
Yu-Jin Zhang |
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ISBN |
978-1-6152-0991-0 |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ DoR2011 |
Serial |
1751 |
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Permanent link to this record |
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Author |
Xavier Perez Sala; Cecilio Angulo; Sergio Escalera |
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Title |
Biologically Inspired Turn Control in Robot Navigation |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th Congrès Català en Intel·ligencia Artificial |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
187-196 |
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Abstract |
An exportable and robust system for turn control using only camera images is proposed for path execution in robot navigation. Robot motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames in the image sequence. This information is used to compute the instantaneous rotation angle. Finally, control loop is closed correcting robot displacements when it is requested for a turn command. The proposed system has been successfully tested on the four-legged Sony Aibo robot. |
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Address |
Lleida |
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ISBN |
978-1-60750-841-0 |
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Conference |
CCIA |
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Notes |
HuPBA;MILAB |
Approved |
no |
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Call Number |
Admin @ si @ PAE2011a |
Serial |
1753 |
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Permanent link to this record |
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Author |
Antonio Hernandez; Carlo Gatta; Laura Igual; Sergio Escalera; Petia Radeva |
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Title |
Automatic Angiography Segmentation Based on Improved Graph-cut |
Type |
Conference Article |
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Year |
2011 |
Publication |
Jornada TIC Salut Girona |
Abbreviated Journal |
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Conference |
TICGI |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ HGI2011 |
Serial |
1754 |
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Permanent link to this record |
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Author |
Laura Igual; Antonio Hernandez; Sergio Escalera; Miguel Reyes; Josep Moya; Joan Carles Soliva; Jordi Faquet; Oscar Vilarroya; Petia Radeva |
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Title |
Automatic Techniques for Studying Attention-Deficit/Hyperactivity Disorder |
Type |
Conference Article |
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Year |
2011 |
Publication |
Jornada TIC Salut Girona |
Abbreviated Journal |
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Admin @ si @ IHE2011 |
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David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin |
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Cool world: domain adaptation of virtual and real worlds for human detection using active learning |
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2011 |
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NIPS Domain Adaptation Workshop: Theory and Application |
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Pedestrian Detection; Virtual; Domain Adaptation; Active Learning |
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Image based human detection is of paramount interest for different applications. The most promising human detectors rely on discriminatively learnt classifiers, i.e., trained with labelled samples. However, labelling is a manual intensive task, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, in Marin et al. we have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera and the same type of scenario. Accordingly, in Vazquez et al. we cast the problem as one of supervised domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we use an active learning technique. Thus, ultimately our human model is learnt by the combination of virtual- and real-world labelled samples which, to the best of our knowledge, was not done before. Here, we term such combined space cool world. In this extended abstract we summarize our proposal, and include quantitative results from Vazquez et al. showing its validity. |
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Granada, Spain |
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ADAS |
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