| |
Records |
Links |
|
Author |
Jaume Gibert |
|
| |
Title |
Vector Space Embedding of Graphs via Statistics of Labelling Information |
Type |
Book Whole |
| |
Year  |
2012 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Pattern recognition is the task that aims at distinguishing objects among different classes. When such a task wants to be solved in an automatic way a crucial step is how to formally represent such patterns to the computer. Based on the different representational formalisms, we may distinguish between statistical and structural pattern recognition. The former describes objects as a set of measurements arranged in the form of what is called a feature vector. The latter assumes that relations between parts of the underlying objects need to be explicitly represented and thus it uses relational structures such as graphs for encoding their inherent information. Vector spaces are a very flexible mathematical structure that has allowed to come up with several efficient ways for the analysis of patterns under the form of feature vectors. Nevertheless, such a representation cannot explicitly cope with binary relations between parts of the objects and it is restricted to measure the exact same number of features for each pattern under study regardless of their complexity. Graph-based representations present the contrary situation. They can easily adapt to the inherent complexity of the patterns but introduce a problem of high computational complexity, hindering the design of efficient tools to process and analyse patterns.
Solving this paradox is the main goal of this thesis. The ideal situation for solving pattern recognition problems would be to represent the patterns using relational structures such as graphs, and to be able to use the wealthy repository of data processing tools from the statistical pattern recognition domain. An elegant solution to this problem is to transform the graph domain into a vector domain where any processing algorithm can be applied. In other words, by mapping each graph to a point in a vector space we automatically get access to the rich set of algorithms from the statistical domain to be applied in the graph domain. Such methodology is called graph embedding.
In this thesis we propose to associate feature vectors to graphs in a simple and very efficient way by just putting attention on the labelling information that graphs store. In particular, we count frequencies of node labels and of edges between labels. Although their locality, these features are able to robustly represent structurally global properties of graphs, when considered together in the form of a vector. We initially deal with the case of discrete attributed graphs, where features are easy to compute. The continuous case is tackled as a natural generalization of the discrete one, where rather than counting node and edge labelling instances, we count statistics of some representatives of them. We encounter how the proposed vectorial representations of graphs suffer from high dimensionality and correlation among components and we face these problems by feature selection algorithms. We also explore how the diversity of different embedding representations can be exploited in order to boost the performance of base classifiers in a multiple classifier systems framework. An extensive experimental evaluation finally shows how the methodology we propose can be efficiently computed and compete with other graph matching and embedding methodologies. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
Ph.D. thesis |
|
| |
Publisher |
Ediciones Graficas Rey |
Place of Publication |
|
Editor |
Ernest Valveny |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ Gib2012 |
Serial |
2204 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Nuria Cirera |
|
| |
Title |
Recognition of Handwritten Historical Documents |
Type |
Report |
| |
Year |
2012 |
Publication |
CVC Technical Report |
Abbreviated Journal |
|
|
| |
Volume |
174 |
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
Master's 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 |
|
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ Cir2012 |
Serial |
2416 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Ariel Amato; Angel Sappa; Alicia Fornes; Felipe Lumbreras; Josep Llados |
|
| |
Title |
Divide and Conquer: Atomizing and Parallelizing A Task in A Mobile Crowdsourcing Platform |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
2nd International ACM Workshop on Crowdsourcing for Multimedia |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
21-22 |
|
| |
Keywords |
|
|
| |
Abstract |
In this paper we present some conclusions about the advantages of having an efficient task formulation when a crowdsourcing platform is used. In particular we show how the task atomization and distribution can help to obtain results in an efficient way. Our proposal is based on a recursive splitting of the original task into a set of smaller and simpler tasks. As a result both more accurate and faster solutions are obtained. Our evaluation is performed on a set of ancient documents that need to be digitized. |
|
| |
Address |
Barcelona; October 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 |
978-1-4503-2396-3 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CrowdMM |
|
| |
Notes |
ADAS; ISE; DAG; 600.054; 600.055; 600.045; 600.061; 602.006 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ SLA2013 |
Serial |
2335 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados |
|
| |
Title |
Plausibility-Graphs for Symbol Spotting in Graphical Documents |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Graph representation of graphical documents often suffers from noise viz. spurious nodes and spurios edges of graph and their discontinuity etc. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance.
But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical
graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset. |
|
| |
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; 601.152 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BDJ2013 |
Serial |
2360 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
|
| |
Title |
Near Convex Region Adjacency Graph and Approximate Neighborhood String Matching for Symbol Spotting in Graphical Documents |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
1078-1082 |
|
| |
Keywords |
|
|
| |
Abstract |
This paper deals with a subgraph matching problem in Region Adjacency Graph (RAG) applied to symbol spotting in graphical documents. RAG is a very important, efficient and natural way of representing graphical information with a graph but this is limited to cases where the information is well defined with perfectly delineated regions. What if the information we are interested in is not confined within well defined regions? This paper addresses this particular problem and solves it by defining near convex grouping of oriented line segments which results in near convex regions. Pure convexity imposes hard constraints and can not handle all the cases efficiently. Hence to solve this problem we have defined a new type of convexity of regions, which allows convex regions to have concavity to some extend. We call this kind of regions Near Convex Regions (NCRs). These NCRs are then used to create the Near Convex Region Adjacency Graph (NCRAG) and with this representation we have formulated the problem of symbol spotting in graphical documents as a subgraph matching problem. For subgraph matching we have used the Approximate Edit Distance Algorithm (AEDA) on the neighborhood string, which starts working after finding a key node in the input or target graph and iteratively identifies similar nodes of the query graph in the neighborhood of the key node. The experiments are performed on artificial, real and distorted datasets. |
|
| |
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; 600.045; 600.056; 600.061; 601.152 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DLB2013a |
Serial |
2358 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
|
| |
Title |
A Product graph based method for dual subgraph matching applied to symbol spotting |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Product graph has been shown to be an efficient way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. This paper focuses on the two major limitations of the previous version of product graph: (1) Spurious nodes and edges in the graph representation and (2) Inefficient node and edge attributes. To deal with noisy information of vectorized graphical documents, we consider a dual graph representation on the original graph representing the graphical information and the product graph is computed between the dual graphs of the query graphs and the input graph.
The dual graph with redundant edges is helpful for efficient and tolerating encoding of the structural information of the graphical documents. The adjacency matrix of the product graph locates similar path information of two graphs and exponentiating the adjacency matrix finds similar paths of greater lengths. Nodes joining similar paths between two graphs are found by combining different exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging. |
|
| |
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 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DLB2013b |
Serial |
2359 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Kaida Xiao; Chenyang Fu; D.Mylonas; Dimosthenis Karatzas; S. Wuerger |
|
| |
Title |
Unique Hue Data for Colour Appearance Models. Part ii: Chromatic Adaptation Transform |
Type |
Journal Article |
| |
Year |
2013 |
Publication |
Color Research & Application |
Abbreviated Journal |
CRA |
|
| |
Volume |
38 |
Issue |
1 |
Pages |
22-29 |
|
| |
Keywords |
|
|
| |
Abstract |
Unique hue settings of 185 observers under three room-lighting conditions were used to evaluate the accuracy of full and mixed chromatic adaptation transform models of CIECAM02 in terms of unique hue reproduction. Perceptual hue shifts in CIECAM02 were evaluated for both models with no clear difference using the current Commission Internationale de l'Éclairage (CIE) recommendation for mixed chromatic adaptation ratio. Using our large dataset of unique hue data as a benchmark, an optimised parameter is proposed for chromatic adaptation under mixed illumination conditions that produces more accurate results in unique hue reproduction. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013 |
|
| |
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 |
|
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ XFM2013 |
Serial |
1822 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
V.C.Kieu; Alicia Fornes; M. Visani; N.Journet ; Anjan Dutta |
|
| |
Title |
The ICDAR/GREC 2013 Music Scores Competition on Staff Removal |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
Competition; Music scores; Staff Removal |
|
| |
Abstract |
The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we propose a staff removal competition where we simulate old music scores. Thus, we have created a new set of images, which contain noise and 3D distortions. This paper describes the distortion methods, metrics, the participant’s methods and the obtained results. |
|
| |
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 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ KFV2013 |
Serial |
2337 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
M. Visani; V.C.Kieu; Alicia Fornes; N.Journet |
|
| |
Title |
The ICDAR 2013 Music Scores Competition: Staff Removal |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
1439-1443 |
|
| |
Keywords |
|
|
| |
Abstract |
The first competition on music scores that was organized at ICDAR in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario: old music scores. For this purpose, we have generated a new set of images using two kinds of degradations: local noise and 3D distortions. This paper describes the dataset, distortion methods, evaluation metrics, the participant's methods and the obtained results. |
|
| |
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; 600.045; 600.061 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ VKF2013 |
Serial |
2338 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados |
|
| |
Title |
Classification of Administrative Document Images by Logo Identification |
Type |
Conference Article |
| |
Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. |
|
| |
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; 600.056; 600.045; 605.203 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ |
Serial |
2348 |
|
| Permanent link to this record |
