| Records |
| Author |
David Geronimo; Antonio Lopez |
| Title |
Vision-based Pedestrian Protection Systems for Intelligent Vehicles |
Type |
Book Whole |
| Year |
2014 |
Publication |
SpringerBriefs in Computer Science |
Abbreviated Journal |
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| Volume |
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Issue |
|
Pages |
1-114 |
| Keywords |
Computer Vision; Driver Assistance Systems; Intelligent Vehicles; Pedestrian Detection; Vulnerable Road Users |
| Abstract |
Pedestrian Protection Systems (PPSs) are on-board systems aimed at detecting and tracking people in the surroundings of a vehicle in order to avoid potentially dangerous situations. These systems, together with other Advanced Driver Assistance Systems (ADAS) such as lane departure warning or adaptive cruise control, are one of the most promising ways to improve traffic safety. By the use of computer vision, cameras working either in the visible or infra-red spectra have been demonstrated as a reliable sensor to perform this task. Nevertheless, the variability of human’s appearance, not only in terms of clothing and sizes but also as a result of their dynamic shape, makes pedestrians one of the most complex classes even for computer vision. Moreover, the unstructured changing and unpredictable environment in which such on-board systems must work makes detection a difficult task to be carried out with the demanded robustness. In this brief, the state of the art in PPSs is introduced through the review of the most relevant papers of the last decade. A common computational architecture is presented as a framework to organize each method according to its main contribution. More than 300 papers are referenced, most of them addressing pedestrian detection and others corresponding to the descriptors (features), pedestrian models, and learning machines used. In addition, an overview of topics such as real-time aspects, systems benchmarking and future challenges of this research area are presented. |
| Address |
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| Corporate Author |
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Thesis |
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Publisher  |
Springer Briefs in Computer Vision |
Place of Publication |
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Editor |
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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 |
978-1-4614-7986-4 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
ADAS; 600.076 |
Approved |
no |
| Call Number |
GeL2014 |
Serial |
2325 |
| Permanent link to this record |
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| |
| Author |
Lluis Pere de las Heras; Ahmed Sheraz; Marcus Liwicki; Ernest Valveny; Gemma Sanchez |
| Title |
Statistical Segmentation and Structural Recognition for Floor Plan Interpretation |
Type |
Journal Article |
| Year |
2014 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
| Volume |
17 |
Issue |
3 |
Pages |
221-237 |
| Keywords |
|
| Abstract |
A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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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 |
1433-2833 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; ADAS; 600.076; 600.077 |
Approved |
no |
| Call Number |
HSL2014 |
Serial |
2370 |
| Permanent link to this record |
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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 |
|
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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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Bart Lamiroy; Jean-Marc Ogier |
| 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 |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ DLB2014 |
Serial |
2698 |
| Permanent link to this record |
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| Author |
Ariel Amato; Ivan Huerta; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez |
| Title |
Moving Cast Shadows Detection Methods for Video Surveillance Applications |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Augmented Vision and Reality |
Abbreviated Journal |
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| Volume |
6 |
Issue |
|
Pages |
23-47 |
| Keywords |
|
| Abstract |
Moving cast shadows are a major concern in today’s performance from broad range of many vision-based surveillance applications because they highly difficult the object classification task. Several shadow detection methods have been reported in the literature during the last years. They are mainly divided into two domains. One usually works with static images, whereas the second one uses image sequences, namely video content. In spite of the fact that both cases can be analogously analyzed, there is a difference in the application field. The first case, shadow detection methods can be exploited in order to obtain additional geometric and semantic cues about shape and position of its casting object (‘shape from shadows’) as well as the localization of the light source. While in the second one, the main purpose is usually change detection, scene matching or surveillance (usually in a background subtraction context). Shadows can in fact modify in a negative way the shape and color of the target object and therefore affect the performance of scene analysis and interpretation in many applications. This chapter wills mainly reviews shadow detection methods as well as their taxonomies related with the second case, thus aiming at those shadows which are associated with moving objects (moving shadows). |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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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 |
2190-5916 |
ISBN |
978-3-642-37840-9 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
ISE; 605.203; 600.049; 302.018; 302.012; 600.078 |
Approved |
no |
| Call Number |
Admin @ si @ AHM2014 |
Serial |
2223 |
| Permanent link to this record |
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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 |
| Keywords |
|
| 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 |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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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 |
0932-8092 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
ISE; 600.078 |
Approved |
no |
| Call Number |
BGS2014a |
Serial |
2411 |
| Permanent link to this record |
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| Author |
David Fernandez; Josep Llados; Alicia Fornes |
| Title |
A graph-based approach for segmenting touching lines in historical handwritten documents |
Type |
Journal Article |
| Year |
2014 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
| Volume |
17 |
Issue |
3 |
Pages |
293-312 |
| Keywords |
Text line segmentation; Handwritten documents; Document image processing; Historical document analysis |
| Abstract |
Text line segmentation in handwritten documents is an important task in the recognition of historical documents. Handwritten document images contain text lines with multiple orientations, touching and overlapping characters between consecutive text lines and different document structures, making line segmentation a difficult task. In this paper, we present a new approach for handwritten text line segmentation solving the problems of touching components, curvilinear text lines and horizontally overlapping components. The proposed algorithm formulates line segmentation as finding the central path in the area between two consecutive lines. This is solved as a graph traversal problem. A graph is constructed using the skeleton of the image. Then, a path-finding algorithm is used to find the optimum path between text lines. The proposed algorithm has been evaluated on a comprehensive dataset consisting of five databases: ICDAR2009, ICDAR2013, UMD, the George Washington and the Barcelona Marriages Database. The proposed method outperforms the state-of-the-art considering the different types and difficulties of the benchmarking data. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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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 |
1433-2833 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; 600.056; 600.061; 602.006; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ FLF2014 |
Serial |
2459 |
| Permanent link to this record |
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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 |
|
| 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. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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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 |
0932-8092 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
CIC; LAMP; 600.074; 600.079 |
Approved |
no |
| Call Number |
Admin @ si @ KBW2014 |
Serial |
2510 |
| Permanent link to this record |
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| Author |
Marçal Rusiñol; Volkmar Frinken; Dimosthenis Karatzas; Andrew Bagdanov; Josep Llados |
| Title |
Multimodal page classification in administrative document image streams |
Type |
Journal Article |
| Year |
2014 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
| Volume |
17 |
Issue |
4 |
Pages |
331-341 |
| Keywords |
Digital mail room; Multimodal page classification; Visual and textual document description |
| Abstract |
In this paper, we present a page classification application in a banking workflow. The proposed architecture represents administrative document images by merging visual and textual descriptions. The visual description is based on a hierarchical representation of the pixel intensity distribution. The textual description uses latent semantic analysis to represent document content as a mixture of topics. Several off-the-shelf classifiers and different strategies for combining visual and textual cues have been evaluated. A final step uses an n-gram model of the page stream allowing a finer-grained classification of pages. The proposed method has been tested in a real large-scale environment and we report results on a dataset of 70,000 pages. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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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 |
1433-2833 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; LAMP; 600.056; 600.061; 601.240; 601.223; 600.077; 600.079 |
Approved |
no |
| Call Number |
Admin @ si @ RFK2014 |
Serial |
2523 |
| Permanent link to this record |
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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 |
|
| Volume |
8746 |
Issue |
|
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. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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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 |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; ADAS; 600.076; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ HVS2014 |
Serial |
2535 |
| Permanent link to this record |
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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 |
|
| Volume |
8746 |
Issue |
|
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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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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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 |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; ADAS; 600.045; 600.056; 600.061; 600.076; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ HFF2014 |
Serial |
2536 |
| Permanent link to this record |
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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 |
|
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 |
| 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 |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
Medium |
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Expedition |
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Conference |
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| Notes |
DAG; 600.077; 600.061 |
Approved |
no |
| Call Number |
Admin @ si @ FKV2014 |
Serial |
2581 |
| Permanent link to this record |
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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 |
|
Pages |
25-37 |
| Keywords |
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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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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Bart Lamiroy; Jean-Marc Ogier |
| 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 |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; 600.045; 600.056; 600.061; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ BDJ2014 |
Serial |
2699 |
| Permanent link to this record |
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| Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
| Title |
Spotting Graphical Symbols in Camera-Acquired Documents in Real Time |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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| Volume |
8746 |
Issue |
|
Pages |
3-10 |
| Keywords |
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| Abstract |
In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Bart Lamiroy; Jean-Marc Ogier |
| 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 |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; 600.045; 600.055; 600.061; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ RKL2014 |
Serial |
2700 |
| Permanent link to this record |
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| Author |
Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados |
| Title |
Classification of Administrative Document Images by Logo Identification |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
|
| Volume |
8746 |
Issue |
|
Pages |
49-58 |
| Keywords |
Administrative Document Classification; Logo Recognition; Logo Spotting |
| 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 |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Bart Lamiroy; Jean-Marc Ogier |
| Language |
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Summary Language |
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Original Title |
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Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
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Expedition |
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Conference |
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| Notes |
DAG; 600.056; 600.045; 605.203; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ RPK2014 |
Serial |
2701 |
| Permanent link to this record |
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| Author |
Jiaolong Xu; Sebastian Ramos;David Vazquez; Antonio Lopez |
| Title |
Cost-sensitive Structured SVM for Multi-category Domain Adaptation |
Type |
Conference Article |
| Year |
2014 |
Publication |
22nd International Conference on Pattern Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
3886 - 3891 |
| Keywords |
Domain Adaptation; Pedestrian Detection |
| Abstract |
Domain adaptation addresses the problem of accuracy drop that a classifier may suffer when the training data (source domain) and the testing data (target domain) are drawn from different distributions. In this work, we focus on domain adaptation for structured SVM (SSVM). We propose a cost-sensitive domain adaptation method for SSVM, namely COSS-SSVM. In particular, during the re-training of an adapted classifier based on target and source data, the idea that we explore consists in introducing a non-zero cost even for correctly classified source domain samples. Eventually, we aim to learn a more targetoriented classifier by not rewarding (zero loss) properly classified source-domain training samples. We assess the effectiveness of COSS-SSVM on multi-category object recognition. |
| Address |
Stockholm; Sweden; August 2014 |
| Corporate Author |
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Thesis |
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| Publisher |
IEEE |
Place of Publication |
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Editor |
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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 Issue |
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Edition |
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| ISSN |
1051-4651 |
ISBN |
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Expedition |
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Conference |
ICPR |
| Notes |
ADAS; 600.057; 600.054; 601.217; 600.076 |
Approved |
no |
| Call Number |
ADAS @ adas @ XRV2014a |
Serial |
2434 |
| Permanent link to this record |
