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Author |
Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
Title |
Growing Algorithm for Intersection Detection (GRAID) in branching patterns |
Type |
Journal Article |
Year |
2015 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVAP |
Volume |
26 |
Issue |
2 |
Pages |
387-400 |
Keywords |
Bifurcation ; Crossroad; Intersection ;Retina ; Vessel |
Abstract |
Analysis of branching structures represents a very important task in fields such as medical diagnosis, road detection or biometrics. Detecting intersection landmarks Becomes crucial when capturing the structure of a branching pattern. We present a very simple geometrical model to describe intersections in branching structures based on two conditions: Bounded Tangency condition (BT) and Shortest Branch (SB) condition. The proposed model precisely sets a geometrical characterization of intersections and allows us to introduce a new unsupervised operator for intersection extraction. We propose an implementation that handles the consequences of digital domain operation that,unlike existing approaches, is not restricted to a particular scale and does not require the computation of the thinned pattern. The new proposal, as well as other existing approaches in the bibliography, are evaluated in a common framework for the first time. The performance analysis is based on two manually segmented image data sets: DRIVE retinal image database and COLON-VESSEL data set, a newly created data set of vascular content in colonoscopy frames. We have created an intersection landmark ground truth for each data set besides comparing our method in the only existing ground truth. Quantitative results confirm that we are able to outperform state-of-the-art performancelevels with the advantage that neither training nor parameter tuning is needed. |
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;SIAI |
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no |
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Admin @ si @MBS2015 |
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2777 |
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Author |
Fahad Shahbaz Khan; Shida Beigpour; Joost Van de Weijer; Michael Felsberg |
Title |
Painting-91: A Large Scale Database for Computational Painting Categorization |
Type |
Journal Article |
Year |
2014 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVAP |
Volume |
25 |
Issue |
6 |
Pages |
1385-1397 |
Keywords |
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Abstract |
Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary research domain. Most of the research in the analysis of paintings involve medium to small range datasets with own specific settings. Interestingly, significant progress has been made in the field of object and scene recognition lately. A key factor in this success is the introduction and availability of benchmark datasets for evaluation. Surprisingly, such a benchmark setup is still missing in the area of computational painting categorization. In this work, we propose a novel large scale dataset of digital paintings. The dataset consists of paintings from 91 different painters. We further show three applications of our dataset namely: artist categorization, style classification and saliency detection. We investigate how local and global features popular in image classification perform for the tasks of artist and style categorization. For both categorization tasks, our experimental results suggest that combining multiple features significantly improves the final performance. We show that state-of-the-art computer vision methods can correctly classify 50 % of unseen paintings to its painter in a large dataset and correctly attribute its artistic style in over 60 % of the cases. Additionally, we explore the task of saliency detection on paintings and show experimental findings using state-of-the-art saliency estimation algorithms. |
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Springer Berlin Heidelberg |
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0932-8092 |
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CIC; LAMP; 600.074; 600.079 |
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no |
Call Number |
Admin @ si @ KBW2014 |
Serial |
2510 |
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Author |
Thierry Brouard; Jordi Gonzalez; Caifeng Shan; Massimo Piccardi; Larry S. Davis |
Title |
Special issue on background modeling for foreground detection in real-world dynamic scenes |
Type |
Journal Article |
Year |
2014 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVAP |
Volume |
25 |
Issue |
5 |
Pages |
1101-1103 |
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Abstract |
Although background modeling and foreground detection are not mandatory steps for computer vision applications, they may prove useful as they separate the primal objects usually called “foreground” from the remaining part of the scene called “background”, and permits different algorithmic treatment in the video processing field such as video surveillance, optical motion capture, multimedia applications, teleconferencing and human–computer interfaces. Conventional background modeling methods exploit the temporal variation of each pixel to model the background, and the foreground detection is made using change detection. The last decade witnessed very significant publications on background modeling but recently new applications in which background is not static, such as recordings taken from mobile devices or Internet videos, need new developments to detect robustly moving objects in challenging environments. Thus, effective methods for robustness to deal both with dynamic backgrounds, i |
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Springer Berlin Heidelberg |
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0932-8092 |
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ISE; 600.078 |
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no |
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BGS2014a |
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2411 |
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Author |
Bogdan Raducanu; Fadi Dornaika |
Title |
Texture-independent recognition of facial expressions in image snapshots and videos |
Type |
Journal Article |
Year |
2013 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
Volume |
24 |
Issue |
4 |
Pages |
811-820 |
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Abstract |
This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines. |
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Springer-Verlag |
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0932-8092 |
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Notes |
OR; 600.046; 605.203;MV |
Approved |
no |
Call Number |
Admin @ si @ RaD2013 |
Serial |
2230 |
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Author |
Dani Rowe; Jordi Gonzalez; Marco Pedersoli; Juan J. Villanueva |
Title |
On Tracking Inside Groups |
Type |
Journal Article |
Year |
2010 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
Volume |
21 |
Issue |
2 |
Pages |
113–127 |
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This work develops a new architecture for multiple-target tracking in unconstrained dynamic scenes, which consists of a detection level which feeds a two-stage tracking system. A remarkable characteristic of the system is its ability to track several targets while they group and split, without using 3D information. Thus, special attention is given to the feature-selection and appearance-computation modules, and to those modules involved in tracking through groups. The system aims to work as a stand-alone application in complex and dynamic scenarios. No a-priori knowledge about either the scene or the targets, based on a previous training period, is used. Hence, the scenario is completely unknown beforehand. Successful tracking has been demonstrated in well-known databases of both indoor and outdoor scenarios. Accurate and robust localisations have been yielded during long-term target merging and occlusions. |
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Springer-Verlag |
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0932-8092 |
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Notes |
ISE |
Approved |
no |
Call Number |
ISE @ ise @ RGP2010 |
Serial |
1158 |
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Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
Title |
Traffic sign recognition system with β -correction |
Type |
Journal Article |
Year |
2010 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
Volume |
21 |
Issue |
2 |
Pages |
99–111 |
Keywords |
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Abstract |
Traffic sign classification represents a classical application of multi-object recognition processing in uncontrolled adverse environments. Lack of visibility, illumination changes, and partial occlusions are just a few problems. In this paper, we introduce a novel system for multi-class classification of traffic signs based on error correcting output codes (ECOC). ECOC is based on an ensemble of binary classifiers that are trained on bi-partition of classes. We classify a wide set of traffic signs types using robust error correcting codings. Moreover, we introduce the novel β-correction decoding strategy that outperforms the state-of-the-art decoding techniques, classifying a high number of classes with great success. |
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Springer-Verlag |
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0932-8092 |
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MILAB;HUPBA |
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no |
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BCNPCL @ bcnpcl @ EPR2010a |
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1276 |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
Title |
Mathematical modeling of G protein-coupled receptor function: What can we learn from empirical and mechanistic models? |
Type |
Book Chapter |
Year |
2014 |
Publication |
G Protein-Coupled Receptors – Modeling and Simulation Advances in Experimental Medicine and Biology |
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Volume |
796 |
Issue |
3 |
Pages |
159-181 |
Keywords |
β-arrestin; biased agonism; curve fitting; empirical modeling; evolutionary algorithm; functional selectivity; G protein; GPCR; Hill coefficient; intrinsic efficacy; inverse agonism; mathematical modeling; mechanistic modeling; operational model; parameter optimization; receptor dimer; receptor oligomerization; receptor constitutive activity; signal transduction; two-state model |
Abstract |
Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists. |
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Springer Netherlands |
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ISSN |
0065-2598 |
ISBN |
978-94-007-7422-3 |
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Notes |
IAM; 600.075 |
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no |
Call Number |
IAM @ iam @ RGG2014 |
Serial |
2197 |
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Author |
Carles Fernandez; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca |
Title |
Towards Ontological Cognitive System |
Type |
Book Chapter |
Year |
2013 |
Publication |
Topics in Medical Image Processing and Computational Vision |
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8 |
Issue |
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Pages |
87-99 |
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Abstract |
The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. This raises a series of technological demands for automatic video understanding and management, which together with the compromising attentional limitations of human operators, have motivated the research community to guide its steps towards a better attainment of such capabilities. As a result, current trends on cognitive vision promise to recognize complex events and self-adapt to different environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users. |
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Springer Netherlands |
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2212-9391 |
ISBN |
978-94-007-0725-2 |
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Notes |
ISE; 605.203; 302.018; 600.049 |
Approved |
no |
Call Number |
Admin @ si @ FGT2013 |
Serial |
2287 |
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Author |
Monica Piñol; Angel Sappa; Ricardo Toledo |
Title |
MultiTable Reinforcement for Visual Object Recognition |
Type |
Conference Article |
Year |
2012 |
Publication |
4th International Conference on Signal and Image Processing |
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221 |
Issue |
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469-480 |
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This paper presents a bag of feature based method for visual object recognition. Our contribution is focussed on the selection of the best feature descriptor. It is implemented by using a novel multi-table reinforcement learning method that selects among five of classical descriptors (i.e., Spin, SIFT, SURF, C-SIFT and PHOW) the one that best describes each image. Experimental results and comparisons are provided showing the improvements achieved with the proposed approach. |
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Coimbatore, India |
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Springer India |
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LNCS |
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1876-1100 |
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978-81-322-0996-6 |
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ICSIP |
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ADAS |
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no |
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Admin @ si @ PST2012 |
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2157 |
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Author |
Naveen Onkarappa; Sujay M. Veerabhadrappa; Angel Sappa |
Title |
Optical Flow in Onboard Applications: A Study on the Relationship Between Accuracy and Scene Texture |
Type |
Conference Article |
Year |
2012 |
Publication |
4th International Conference on Signal and Image Processing |
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Volume |
221 |
Issue |
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257-267 |
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Optical flow has got a major role in making advanced driver assistance systems (ADAS) a reality. ADAS applications are expected to perform efficiently in all kinds of environments, those are highly probable, that one can drive the vehicle in different kinds of roads, times and seasons. In this work, we study the relationship of optical flow with different roads, that is by analyzing optical flow accuracy on different road textures. Texture measures such as TeX , TeX and TeX are evaluated for this purpose. Further, the relation of regularization weight to the flow accuracy in the presence of different textures is also analyzed. Additionally, we present a framework to generate synthetic sequences of different textures in ADAS scenarios with ground-truth optical flow. |
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Coimbatore, India |
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1876-1100 |
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978-81-322-0996-6 |
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ICSIP |
Notes |
ADAS |
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no |
Call Number |
Admin @ si @ OVS2012 |
Serial |
2356 |
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Author |
Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez |
Title |
Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies |
Type |
Book Chapter |
Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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Volume |
8746 |
Issue |
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Pages |
109-121 |
Keywords |
Graphics recognition; Floor plan analysis; Object segmentation |
Abstract |
In this paper we present a wall segmentation approach in floor plans that is able to work independently to the graphical notation, does not need any pre-annotated data for learning, and is able to segment multiple-shaped walls such as beams and curved-walls. This method results from the combination of the wall segmentation approaches [3, 5] presented recently by the authors. Firstly, potential straight wall segments are extracted in an unsupervised way similar to [3], but restricting even more the wall candidates considered in the original approach. Then, based on [5], these segments are used to learn the texture pattern of walls and spot the lost instances. The presented combination of both methods has been tested on 4 available datasets with different notations and compared qualitatively and quantitatively to the state-of-the-art applied on these collections. Additionally, some qualitative results on floor plans directly downloaded from the Internet are reported in the paper. The overall performance of the method demonstrates either its adaptability to different wall notations and shapes, and to document qualities and resolutions. |
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Springer Berlin Heidelberg |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
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Notes |
DAG; ADAS; 600.076; 600.077 |
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no |
Call Number |
Admin @ si @ HVS2014 |
Serial |
2535 |
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Author |
Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados |
Title |
Hierarchical Plausibility-Graphs for Symbol Spotting in Graphical Documents |
Type |
Book Chapter |
Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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Volume |
8746 |
Issue |
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Pages |
25-37 |
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Abstract |
Graph representation of graphical documents often suffers from noise such as spurious nodes and edges, and their discontinuity. 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. |
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Springer Berlin Heidelberg |
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Editor |
Bart Lamiroy; Jean-Marc Ogier |
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LNCS |
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0302-9743 |
ISBN |
978-3-662-44853-3 |
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Notes |
DAG; 600.045; 600.056; 600.061; 600.077 |
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no |
Call Number |
Admin @ si @ BDJ2014 |
Serial |
2699 |
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Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
Title |
A Product Graph Based Method for Dual Subgraph Matching Applied to Symbol Spotting |
Type |
Book Chapter |
Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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Volume |
8746 |
Issue |
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Pages |
7-11 |
Keywords |
Product graph; Dual edge graph; Subgraph matching; Random walks; Graph kernel |
Abstract |
Product graph has been shown as a way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. Here we focus on the two major limitations of the previous version of the algorithm: (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 edge graph representation on the original graph representing the graphical information and the product graph is computed between the dual edge graphs of the pattern graph and the target graph. The dual edge 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 the pair of similar edges of two operand graphs and exponentiating the adjacency matrix finds similar random walks of greater lengths. Nodes joining similar random walks between two graphs are found by combining different weighted exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging. |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Bart Lamiroy; Jean-Marc Ogier |
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LNCS |
Series Volume |
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0302-9743 |
ISBN |
978-3-662-44853-3 |
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Notes |
DAG; 600.077 |
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no |
Call Number |
Admin @ si @ DLB2014 |
Serial |
2698 |
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Author |
Alicia Fornes; V.C.Kieu; M. Visani; N.Journet; Anjan Dutta |
Title |
The ICDAR/GREC 2013 Music Scores Competition: Staff Removal |
Type |
Book Chapter |
Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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Volume |
8746 |
Issue |
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Pages |
207-220 |
Keywords |
Competition; Graphics recognition; Music scores; Writer identification; 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 in both staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario concerning old and degraded music scores. For this purpose, we have generated a new set of semi-synthetic images using two degradation models that we previously introduced: local noise and 3D distortions. In this extended paper we provide an extended description of the dataset, degradation models, evaluation metrics, the participant’s methods and the obtained results that could not be presented at ICDAR and GREC proceedings due to page limitations. |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
B.Lamiroy; J.-M. Ogier |
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Series Editor |
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Abbreviated Series Title |
LNCS |
Series Volume |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
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Notes |
DAG; 600.077; 600.061 |
Approved |
no |
Call Number |
Admin @ si @ FKV2014 |
Serial |
2581 |
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Author |
Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados |
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 |
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Volume |
8746 |
Issue |
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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. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-662-44853-3 |
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DAG; ADAS; 600.045; 600.056; 600.061; 600.076; 600.077 |
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Admin @ si @ HFF2014 |
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2536 |
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