| |
Records |
Links |
|
Author  |
Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis |
|
| |
Title |
3D Gait Estimation from Monoscopic Video |
Type |
Miscellaneous |
| |
Year |
2004 |
Publication |
IEEE International Conference on Image Processing |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Singapore |
|
| |
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 |
ADAS |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ SAM2004c |
Serial |
495 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis |
|
| |
Title |
Monocular 3D Human Body Reconstruction Towards Depth Augmentation of Television Sequences |
Type |
Conference Article |
| |
Year |
2003 |
Publication |
IEEE International Conference on Image Processing, Barcelona, Spain, September 2003 |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
325-328 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Barcelona |
|
| |
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 |
ADAS |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ SAM2003 |
Serial |
418 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Angel Sappa; Niki Aifanti; Sotiris Malassiotis; N. Grammalidis |
|
| |
Title |
Survey of 3D Human Body Representations |
Type |
Book Chapter |
| |
Year |
2005 |
Publication |
Encyclopedia of Information Science and Technology, 1(5):2696–2701 |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
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 |
|
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ SAM2005a |
Serial |
497 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Angel Sappa; P. Carvajal; Cristhian A. Aguilera-Carrasco; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla |
|
| |
Title |
Wavelet based visible and infrared image fusion: a comparative study |
Type |
Journal Article |
| |
Year |
2016 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
|
| |
Volume |
16 |
Issue |
6 |
Pages |
1-15 |
|
| |
Keywords |
Image fusion; fusion evaluation metrics; visible and infrared imaging; discrete wavelet transform |
|
| |
Abstract |
This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and Long Wave InfraRed (LWIR). |
|
| |
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 |
ADAS; 600.086; 600.076 |
Approved |
no |
|
| |
Call Number |
Admin @ si @SCA2016 |
Serial |
2807 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Angel Sappa; Patricia Suarez; Henry Velesaca; Dario Carpio |
|
| |
Title |
Domain Adaptation in Image Dehazing: Exploring the Usage of Images from Virtual Scenarios |
Type |
Conference Article |
| |
Year |
2022 |
Publication |
16th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
85-92 |
|
| |
Keywords |
Domain adaptation; Synthetic hazed dataset; Dehazing |
|
| |
Abstract |
This work presents a novel domain adaptation strategy for deep learning-based approaches to solve the image dehazing
problem. Firstly, a large set of synthetic images is generated by using a realistic 3D graphic simulator; these synthetic
images contain different densities of haze, which are used for training the model that is later adapted to any real scenario.
The adaptation process requires just a few images to fine-tune the model parameters. The proposed strategy allows
overcoming the limitation of training a given model with few images. In other words, the proposed strategy implements
the adaptation of a haze removal model trained with synthetic images to real scenarios. It should be noticed that it is quite
difficult, if not impossible, to have large sets of pairs of real-world images (with and without haze) to train in a supervised
way dehazing algorithms. Experimental results are provided showing the validity of the proposed domain adaptation
strategy. |
|
| |
Address |
Lisboa; Portugal; July 2022 |
|
| |
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 |
CGVCVIP |
|
| |
Notes |
MSIAU; no proj |
Approved |
no |
|
| |
Call Number |
Admin @ si @ SSV2022 |
Serial |
3804 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Angel Sappa; Rosa Herrero; Fadi Dornaika; David Geronimo; Antonio Lopez |
|
| |
Title |
Road Approximation in Euclidean and v-Disparity Space: A Comparative Study |
Type |
Conference Article |
| |
Year |
2007 |
Publication |
Computer Aided Systems Theory, |
Abbreviated Journal |
|
|
| |
Volume |
4739 |
Issue |
|
Pages |
1105–1112 |
|
| |
Keywords |
|
|
| |
Abstract |
This paper presents a comparative study between two road approximation techniques—planar surfaces—from stereo vision data. The first approach is carried out in the v-disparity space and is based on a voting scheme, the Hough transform. The second one consists in computing the best fitting plane for the whole 3D road data points, directly in the Euclidean space, by using least squares fitting. The comparative study is initially performed over a set of different synthetic surfaces
(e.g., plane, quadratic surface, cubic surface) digitized by a virtual stereo head; then real data obtained with a commercial stereo head are used. The comparative study is intended to be used as a criterion for fining the best technique according to the road geometry. Additionally, it highlights common problems driven from a wrong assumption about the scene’s prior knowledge. |
|
| |
Address |
Las Palmas de Gran Canaria (Spain) |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
EUROCAST |
|
| |
Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ SHD2007b |
Serial |
917 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Angel Sappa; Rosa Herrero; Fadi Dornaika; David Geronimo; Antonio Lopez |
|
| |
Title |
Road Approximation in Euclidean and v-Disparity Space: A Comparative Study |
Type |
Conference Article |
| |
Year |
2007 |
Publication |
EUROCAST2007, Workshop on Cybercars and Intelligent Vehicles |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
368–369 |
|
| |
Keywords |
|
|
| |
Abstract |
This paper presents a comparative study between two road approximation techniques—planar surfaces—from stereo vision data. The first approach is carried out in the v-disparity space and is based on a voting scheme, the Hough transform. The second one consists in computing the best fitting plane for the whole 3D road data points, directly in the Euclidean space, by using least squares fitting. The comparative study is initially performed over a set of different synthetic surfaces
(e.g., plane, quadratic surface, cubic surface) digitized by a virtual stereo head; then real data obtained with a commercial stereo head are used. The comparative study is intended to be used as a criterion for fining the best technique according to the road geometry. Additionally, it highlights common problems driven from a wrong assumption about the scene’s prior knowledge. |
|
| |
Address |
Las Palmas de Gran Canaria (Spain) |
|
| |
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 |
ADAS |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ SHD2007a |
Serial |
936 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Angel Valencia; Roger Idrovo; Angel Sappa; Douglas Plaza; Daniel Ochoa |
|
| |
Title |
A 3D Vision Based Approach for Optimal Grasp of Vacuum Grippers |
Type |
Conference Article |
| |
Year |
2017 |
Publication |
IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
In general, robot grasping approaches are based on the usage of multi-finger grippers. However, when large size objects need to be manipulated vacuum grippers are preferred, instead of finger based grippers. This paper aims to estimate the best picking place for a two suction cups vacuum gripper,
when planar objects with an unknown size and geometry are considered. The approach is based on the estimation of geometric properties of object’s shape from a partial cloud of points (a single 3D view), in such a way that combine with considerations of a theoretical model to generate an optimal contact point
that minimizes the vacuum force needed to guarantee a grasp.
Experimental results in real scenarios are presented to show the validity of the proposed approach. |
|
| |
Address |
San Sebastian; Spain; May 2017 |
|
| |
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 |
ECMSM |
|
| |
Notes |
ADAS; 600.086; 600.118 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ VIS2017 |
Serial |
2917 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Anguelos Nicolaou; Sounak Dey; V.Christlein; A.Maier; Dimosthenis Karatzas |
|
| |
Title |
Non-deterministic Behavior of Ranking-based Metrics when Evaluating Embeddings |
Type |
Conference Article |
| |
Year |
2018 |
Publication |
International Workshop on Reproducible Research in Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
11455 |
Issue |
|
Pages |
71-82 |
|
| |
Keywords |
|
|
| |
Abstract |
Embedding data into vector spaces is a very popular strategy of pattern recognition methods. When distances between embeddings are quantized, performance metrics become ambiguous. In this paper, we present an analysis of the ambiguity quantized distances introduce and provide bounds on the effect. We demonstrate that it can have a measurable effect in empirical data in state-of-the-art systems. We also approach the phenomenon from a computer security perspective and demonstrate how someone being evaluated by a third party can exploit this ambiguity and greatly outperform a random predictor without even access to the input data. We also suggest a simple solution making the performance metrics, which rely on ranking, totally deterministic and impervious to such exploits. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; 600.121; 600.129 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ NDC2018 |
Serial |
3178 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Aniol Lidon; Marc Bolaños; Mariella Dimiccoli; Petia Radeva; Maite Garolera; Xavier Giro |
|
| |
Title |
Semantic Summarization of Egocentric Photo-Stream Events |
Type |
Conference Article |
| |
Year |
2017 |
Publication |
2nd Workshop on Lifelogging Tools and Applications |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
San Francisco; USA; October 2017 |
|
| |
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 |
978-1-4503-5503-2 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ACMW (LTA) |
|
| |
Notes |
MILAB; no proj |
Approved |
no |
|
| |
Call Number |
Admin @ si @ LBD2017 |
Serial |
3024 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Aniol Lidon; Xavier Giro; Marc Bolaños; Petia Radeva; Markus Seidl; Matthias Zeppelzauer |
|
| |
Title |
UPC-UB-STP @ MediaEval 2015 diversity task: iterative reranking of relevant images |
Type |
Conference Article |
| |
Year |
2015 |
Publication |
2015 MediaEval Retrieving Diverse Images Task |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
This paper presents the results of the UPC-UB-STP team in the 2015 MediaEval Retrieving Diverse Images Task. The goal of the challenge is to provide a ranked list of Flickr photos for a predefined set of queries. Our approach firstly generates a ranking of images based on a query-independent estimation of its relevance. Only top results are kept and iteratively re-ranked based on their intra-similarity to introduce diversity. |
|
| |
Address |
Wurzen; Germany; September 2015 |
|
| |
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 |
MediaEval |
|
| |
Notes |
MILAB |
Approved |
no |
|
| |
Call Number |
Admin @ si @LGB2016 |
Serial |
2793 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Anjan Dutta |
|
| |
Title |
Inexact Subgraph Matching Applied to Symbol Spotting in Graphical Documents |
Type |
Book Whole |
| |
Year |
2014 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
There is a resurgence in the use of structural approaches in the usual object recognition and retrieval problem. Graph theory, in particular, graph matching plays a relevant role in that. Specifically, the detection of an object (or a part of that) in an image in terms of structural features can be formulated as a subgraph matching. Subgraph matching is a challenging task. Specially due to the presence of outliers most of the graph matching algorithms do not perform well in subgraph matching scenario. Also exact subgraph isomorphism has proven to be an NP-complete problem. So naturally, in graph matching community, there are lot of efforts addressing the problem of subgraph matching within suboptimal bound. Most of them work with approximate algorithms that try to get an inexact solution in estimated way. In addition, usual recognition must cope with distortion. Inexact graph matching consists in finding the best isomorphism under a similarity measure. Theoretically this thesis proposes algorithms for solving subgraph matching in an approximate and inexact way.
We consider the symbol spotting problem on graphical documents or line drawings from application point of view. This is a well known problem in the graphics recognition community. It can be further applied for indexing and classification of documents based on their contents. The structural nature of this kind of documents easily motivates one for giving a graph based representation. So the symbol spotting problem on graphical documents can be considered as a subgraph matching problem. The main challenges in this application domain is the noise and distortions that might come during the usage, digitalization and raster to vector conversion of those documents. Apart from that computer vision nowadays is not any more confined within a limited number of images. So dealing a huge number of images with graph based method is a further challenge.
In this thesis, on one hand, we have worked on efficient and robust graph representation to cope with the noise and distortions coming from documents. On the other hand, we have worked on different graph based methods and framework to solve the subgraph matching problem in a better approximated way, which can also deal with considerable number of images. Firstly, we propose a symbol spotting method by hashing serialized subgraphs. Graph serialization allows to create factorized substructures such as graph paths, which can be organized in hash tables depending on the structural similarities of the serialized subgraphs. The involvement of hashing techniques helps to reduce the search space substantially and speeds up the spotting procedure. Secondly, we introduce contextual similarities based on the walk based propagation on tensor product graph. These contextual similarities involve higher order information and more reliable than pairwise similarities. We use these higher order similarities to formulate subgraph matching as a node and edge selection problem in the tensor product graph. Thirdly, we propose near convex grouping to form near convex region adjacency graph which eliminates the limitations of traditional region adjacency graph representation for graphic recognition. Fourthly, we propose a hierarchical graph representation by simplifying/correcting the structural errors to create a hierarchical graph of the base graph. Later these hierarchical graph structures are matched with some graph matching methods. Apart from that, in this thesis we have provided an overall experimental comparison of all the methods and some of the state-of-the-art methods. Furthermore, some dataset models have also been proposed. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
Ph.D. thesis |
|
| |
Publisher |
Ediciones Graficas Rey |
Place of Publication |
|
Editor |
Josep Llados;Umapada Pal |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-84-940902-4-0 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ Dut2014 |
Serial |
2465 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Anjan Dutta |
|
| |
Title |
Symbol Spotting in Graphical Documents by Serialized Subgraph Matching |
Type |
Report |
| |
Year |
2010 |
Publication |
CVC Technical Report |
Abbreviated Journal |
|
|
| |
Volume |
159 |
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 @ Dut2010 |
Serial |
1351 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Anjan Dutta; Hichem Sahbi |
|
| |
Title |
Stochastic Graphlet Embedding |
Type |
Journal Article |
| |
Year |
2018 |
Publication |
IEEE Transactions on Neural Networks and Learning Systems |
Abbreviated Journal |
TNNLS |
|
| |
Volume |
|
Issue |
|
Pages |
1-14 |
|
| |
Keywords |
Stochastic graphlets; Graph embedding; Graph classification; Graph hashing; Betweenness centrality |
|
| |
Abstract |
Graph-based methods are known to be successful in many machine learning and pattern classification tasks. These methods consider semi-structured data as graphs where nodes correspond to primitives (parts, interest points, segments,
etc.) and edges characterize the relationships between these primitives. However, these non-vectorial graph data cannot be straightforwardly plugged into off-the-shelf machine learning algorithms without a preliminary step of – explicit/implicit –graph vectorization and embedding. This embedding process
should be resilient to intra-class graph variations while being highly discriminant. In this paper, we propose a novel high-order stochastic graphlet embedding (SGE) that maps graphs into vector spaces. Our main contribution includes a new stochastic search procedure that efficiently parses a given graph and extracts/samples unlimitedly high-order graphlets. We consider
these graphlets, with increasing orders, to model local primitives as well as their increasingly complex interactions. In order to build our graph representation, we measure the distribution of these graphlets into a given graph, using particular hash functions that efficiently assign sampled graphlets into isomorphic sets with a very low probability of collision. When
combined with maximum margin classifiers, these graphlet-based representations have positive impact on the performance of pattern comparison and recognition as corroborated through extensive experiments using standard benchmark databases. |
|
| |
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; 602.167; 602.168; 600.097; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DuS2018 |
Serial |
3225 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Anjan Dutta; Jaume Gibert; Josep Llados; Horst Bunke; Umapada Pal |
|
| |
Title |
Combination of Product Graph and Random Walk Kernel for Symbol Spotting in Graphical Documents |
Type |
Conference Article |
| |
Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
1663-1666 |
|
| |
Keywords |
|
|
| |
Abstract |
This paper explores the utilization of product graph for spotting symbols on graphical documents. Product graph is intended to find the candidate subgraphs or components in the input graph containing the paths similar to the query graph. The acute angle between two edges and their length ratio are considered as the node labels. In a second step, each of the candidate subgraphs in the input graph is assigned with a distance measure computed by a random walk kernel. Actually it is the minimum of the distances of the component to all the components of the model graph. This distance measure is then used to eliminate dissimilar components. The remaining neighboring components are grouped and the grouped zone is considered as a retrieval zone of a symbol similar to the queried one. The entire method works online, i.e., it doesn't need any preprocessing step. The present paper reports the initial results of the method, which are very encouraging. |
|
| |
Address |
Tsukuba, Japan |
|
| |
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 |
1051-4651 |
ISBN |
978-1-4673-2216-4 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DGL2012 |
Serial |
2125 |
|
| Permanent link to this record |
