|
Records |
Links |
|
Author |
Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez |
|
|
Title |
Domain Adaptation of Deformable Part-Based Models |
Type |
Journal Article |
|
Year |
2014 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
|
|
Volume |
36 |
Issue |
12 |
Pages |
2367-2380 |
|
|
Keywords |
Domain Adaptation; Pedestrian Detection |
|
|
Abstract |
The accuracy of object classifiers can significantly drop when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, adapting the classifiers to the scenario in which they must operate is of paramount importance. We present novel domain adaptation (DA) methods for object detection. As proof of concept, we focus on adapting the state-of-the-art deformable part-based model (DPM) for pedestrian detection. We introduce an adaptive structural SVM (A-SSVM) that adapts a pre-learned classifier between different domains. By taking into account the inherent structure in feature space (e.g., the parts in a DPM), we propose a structure-aware A-SSVM (SA-SSVM). Neither A-SSVM nor SA-SSVM needs to revisit the source-domain training data to perform the adaptation. Rather, a low number of target-domain training examples (e.g., pedestrians) are used. To address the scenario where there are no target-domain annotated samples, we propose a self-adaptive DPM based on a self-paced learning (SPL) strategy and a Gaussian Process Regression (GPR). Two types of adaptation tasks are assessed: from both synthetic pedestrians and general persons (PASCAL VOC) to pedestrians imaged from an on-board camera. Results show that our proposals avoid accuracy drops as high as 15 points when comparing adapted and non-adapted detectors. |
|
|
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 |
0162-8828 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 600.057; 600.054; 601.217; 600.076 |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ XRV2014b |
Serial |
2436 |
|
Permanent link to this record |
|
|
|
|
Author |
Jiaolong Xu; David Vazquez; Antonio Lopez; Javier Marin; Daniel Ponsa |
|
|
Title |
Learning a Part-based Pedestrian Detector in Virtual World |
Type |
Journal Article |
|
Year |
2014 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
|
|
Volume |
15 |
Issue |
5 |
Pages |
2121-2131 |
|
|
Keywords |
Domain Adaptation; Pedestrian Detection; Virtual Worlds |
|
|
Abstract |
Detecting pedestrians with on-board vision systems is of paramount interest for assisting drivers to prevent vehicle-to-pedestrian accidents. The core of a pedestrian detector is its classification module, which aims at deciding if a given image window contains a pedestrian. Given the difficulty of this task, many classifiers have been proposed during the last fifteen years. Among them, the so-called (deformable) part-based classifiers including multi-view modeling are usually top ranked in accuracy. Training such classifiers is not trivial since a proper aspect clustering and spatial part alignment of the pedestrian training samples are crucial for obtaining an accurate classifier. In this paper, first we perform automatic aspect clustering and part alignment by using virtual-world pedestrians, i.e., human annotations are not required. Second, we use a mixture-of-parts approach that allows part sharing among different aspects. Third, these proposals are integrated in a learning framework which also allows to incorporate real-world training data to perform domain adaptation between virtual- and real-world cameras. Overall, the obtained results on four popular on-board datasets show that our proposal clearly outperforms the state-of-the-art deformable part-based detector known as latent SVM. |
|
|
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 |
1931-0587 |
ISBN |
978-1-4673-2754-1 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 600.076 |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ XVL2014 |
Serial |
2433 |
|
Permanent link to this record |
|
|
|
|
Author |
M.J. Yzuel; J. Pladellorens; Joan Serrat; A. Dupuy |
|
|
Title |
Application restauration and edge detection techniques in the calculation of left ventricular volumes. |
Type |
Conference Article |
|
Year |
1993 |
Publication |
Optics in Medicine, Biology and Environmental Research : Selected contributions to the first International Conference on Optics within Life Sciences (OWLS I) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
374-375 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Elsevier |
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 @ YPS1993 |
Serial |
244 |
|
Permanent link to this record |
|
|
|
|
Author |
Antonio Lopez; W. Niessen; Joan Serrat; K. Nikolay; B. Ter Haar Romeny; Juan J. Villanueva; M. Viergerver |
|
|
Title |
New improvements in the multiscale analysis of trabecular bone patterns |
Type |
Book Chapter |
|
Year |
2000 |
Publication |
Pattern Recognition and Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
251-260 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
IOS Press |
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 |
Admin @ si @ |
Serial |
3418 |
|
Permanent link to this record |
|
|
|
|
Author |
Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados |
|
|
Title |
Classification of Administrative Document Images by Logo Identification |
Type |
Conference Article |
|
Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. |
|
|
Address |
Bethlehem; PA; USA; August 2013 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
GREC |
|
|
Notes |
DAG; 600.056; 600.045; 605.203 |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
2348 |
|
Permanent link to this record |
|
|
|
|
Author |
Adriana Romero; Simeon Petkov; Carlo Gatta; M.Sabate; Petia Radeva |
|
|
Title |
Efficient automatic segmentation of vessels |
Type |
Conference Article |
|
Year |
2012 |
Publication |
16th Conference on Medical Image Understanding and Analysis |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Swansea, United Kingdom |
|
|
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 |
MIUA |
|
|
Notes |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
2137 |
|
Permanent link to this record |
|
|
|
|
Author |
Alejandro Gonzalez Alzate; David Vazquez; Antonio Lopez; Jaume Amores |
|
|
Title |
On-Board Object Detection: Multicue, Multimodal, and Multiview Random Forest of Local Experts |
Type |
Journal Article |
|
Year |
2017 |
Publication |
IEEE Transactions on cybernetics |
Abbreviated Journal |
Cyber |
|
|
Volume |
47 |
Issue |
11 |
Pages |
3980 - 3990 |
|
|
Keywords |
Multicue; multimodal; multiview; object detection |
|
|
Abstract |
Despite recent significant advances, object detection continues to be an extremely challenging problem in real scenarios. In order to develop a detector that successfully operates under these conditions, it becomes critical to leverage upon multiple cues, multiple imaging modalities, and a strong multiview (MV) classifier that accounts for different object views and poses. In this paper, we provide an extensive evaluation that gives insight into how each of these aspects (multicue, multimodality, and strong MV classifier) affect accuracy both individually and when integrated together. In the multimodality component, we explore the fusion of RGB and depth maps obtained by high-definition light detection and ranging, a type of modality that is starting to receive increasing attention. As our analysis reveals, although all the aforementioned aspects significantly help in improving the accuracy, the fusion of visible spectrum and depth information allows to boost the accuracy by a much larger margin. The resulting detector not only ranks among the top best performers in the challenging KITTI benchmark, but it is built upon very simple blocks that are easy to implement and computationally efficient. |
|
|
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 |
2168-2267 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 600.085; 600.082; 600.076; 600.118 |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
2810 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Escalera; Jordi Gonzalez; Xavier Baro; Jamie Shotton |
|
|
Title |
Guest Editor Introduction to the Special Issue on Multimodal Human Pose Recovery and Behavior Analysis |
Type |
Journal Article |
|
Year |
2016 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
|
|
Volume |
28 |
Issue |
|
Pages |
1489 - 1491 |
|
|
Keywords |
|
|
|
Abstract |
The sixteen papers in this special section focus on human pose recovery and behavior analysis (HuPBA). This is one of the most challenging topics in computer vision, pattern analysis, and machine learning. It is of critical importance for application areas that include gaming, computer interaction, human robot interaction, security, commerce, assistive technologies and rehabilitation, sports, sign language recognition, and driver assistance technology, to mention just a few. In essence, HuPBA requires dealing with the articulated nature of the human body, changes in appearance due to clothing, and the inherent problems of clutter scenes, such as background artifacts, occlusions, and illumination changes. These papers represent the most recent research in this field, including new methods considering still images, image sequences, depth data, stereo vision, 3D vision, audio, and IMUs, among others. |
|
|
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 |
HuPBA; ISE;MV; |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
2851 |
|
Permanent link to this record |
|
|
|
|
Author |
Pau Riba; Alicia Fornes; Josep Llados |
|
|
Title |
Towards the Alignment of Handwritten Music Scores |
Type |
Conference Article |
|
Year |
2015 |
Publication |
11th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
It is very common to find different versions of the same music work in archives of Opera Theaters. These differences correspond to modifications and annotations from the musicians. From the musicologist point of view, these variations are very interesting and deserve study. This paper explores the alignment of music scores as a tool for automatically detecting the passages that contain such differences. Given the difficulties in the recognition of handwritten music scores, our goal is to align the music scores and at the same time, avoid the recognition of music elements as much as possible. After removing the staff lines, braces and ties, the bar lines are detected. Then, the bar units are described as a whole using the Blurred Shape Model. The bar units alignment is performed by using Dynamic Time Warping. The analysis of the alignment path is used to detect the variations in the music scores. The method has been evaluated on a subset of the CVC-MUSCIMA dataset, showing encouraging results. |
|
|
Address |
Nancy; France; August 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
Bart Lamiroy; Rafael Dueire Lins |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-319-52158-9 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
GREC |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
2874 |
|
Permanent link to this record |
|
|
|
|
Author |
Patricia Suarez; Angel Sappa; Boris X. Vintimilla |
|
|
Title |
Learning to Colorize Infrared Images |
Type |
Conference Article |
|
Year |
2017 |
Publication |
15th International Conference on Practical Applications of Agents and Multi-Agent System |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
CNN in multispectral imaging; Image colorization |
|
|
Abstract |
This paper focuses on near infrared (NIR) image colorization by using a Generative Adversarial Network (GAN) architecture model. The proposed architecture consists of two stages. Firstly, it learns to colorize the given input, resulting in a RGB image. Then, in the second stage, a discriminative model is used to estimate the probability that the generated image came from the training dataset, rather than the image automatically generated. The proposed model starts the learning process from scratch, because our set of images is very dierent from the dataset used in existing pre-trained models, so transfer learning strategies cannot be used. Infrared image colorization is an important problem when human perception need to be considered, e.g, in remote sensing applications. Experimental results with a large set of real images are provided showing the validity of the proposed approach. |
|
|
Address |
Porto; Portugal; June 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 |
PAAMS |
|
|
Notes |
ADAS; MSIAU; 600.086; 600.122; 600.118 |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
2919 |
|
Permanent link to this record |
|
|
|
|
Author |
Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate |
|
|
Title |
Is there a pattern of Chromosome territoriality along mice spermatogenesis? |
Type |
Conference Article |
|
Year |
2017 |
Publication |
3rd Spanish MeioNet Meeting Abstract Book |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
55-56 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Miraflores de la Sierra; Madrid; June 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 |
MEIONET |
|
|
Notes |
IAM; 600.096; 600.145 |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
2958 |
|
Permanent link to this record |
|
|
|
|
Author |
Marc Masana; Joost Van de Weijer; Luis Herranz;Andrew Bagdanov; Jose Manuel Alvarez |
|
|
Title |
Domain-adaptive deep network compression |
Type |
Conference Article |
|
Year |
2017 |
Publication |
17th IEEE International Conference on Computer Vision |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Deep Neural Networks trained on large datasets can be easily transferred to new domains with far fewer labeled examples by a process called fine-tuning. This has the advantage that representations learned in the large source domain can be exploited on smaller target domains. However, networks designed to be optimal for the source task are often prohibitively large for the target task. In this work we address the compression of networks after domain transfer.
We focus on compression algorithms based on low-rank matrix decomposition. Existing methods base compression solely on learned network weights and ignore the statistics of network activations. We show that domain transfer leads to large shifts in network activations and that it is desirable to take this into account when compressing.
We demonstrate that considering activation statistics when compressing weights leads to a rank-constrained regression problem with a closed-form solution. Because our method takes into account the target domain, it can more optimally
remove the redundancy in the weights. Experiments show that our Domain Adaptive Low Rank (DALR) method significantly outperforms existing low-rank compression techniques. With our approach, the fc6 layer of VGG19 can be compressed more than 4x more than using truncated SVD alone – with only a minor or no loss in accuracy. When applied to domain-transferred networks it allows for compression down to only 5-20% of the original number of parameters with only a minor drop in performance. |
|
|
Address |
Venice; Italy; 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 |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICCV |
|
|
Notes |
LAMP; 601.305; 600.106; 600.120 |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
3034 |
|
Permanent link to this record |
|
|
|
|
Author |
Albert Clapes; Ozan Bilici; Dariia Temirova; Egils Avots; Gholamreza Anbarjafari; Sergio Escalera |
|
|
Title |
From apparent to real age: gender, age, ethnic, makeup, and expression bias analysis in real age estimation |
Type |
Conference Article |
|
Year |
2018 |
Publication |
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
2373-2382 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Salt Lake City; USA; June 2018 |
|
|
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 |
CVPRW |
|
|
Notes |
HUPBA |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
3116 |
|
Permanent link to this record |
|
|
|
|
Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
|
|
Title |
Automatic Verification of Properly Signed Multi-page Document Images |
Type |
Conference Article |
|
Year |
2015 |
Publication |
Proceedings of the Eleventh International Symposium on Visual Computing |
Abbreviated Journal |
|
|
|
Volume |
9475 |
Issue |
|
Pages |
327-336 |
|
|
Keywords |
Document Image; Manual Inspection; Signature Verification; Rejection Criterion; Document Flow |
|
|
Abstract |
In this paper we present an industrial application for the automatic screening of incoming multi-page documents in a banking workflow aimed at determining whether these documents are properly signed or not. The proposed method is divided in three main steps. First individual pages are classified in order to identify the pages that should contain a signature. In a second step, we segment within those key pages the location where the signatures should appear. The last step checks whether the signatures are present or not. Our method is tested in a real large-scale environment and we report the results when checking two different types of real multi-page contracts, having in total more than 14,500 pages. |
|
|
Address |
Las Vegas, Nevada, USA; December 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
9475 |
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ISVC |
|
|
Notes |
DAG; 600.077 |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
3189 |
|
Permanent link to this record |
|
|
|
|
Author |
L. Rothacker; Marçal Rusiñol; Josep Llados; G.A. Fink |
|
|
Title |
A Two-stage Approach to Segmentation-Free Query-by-example Word Spotting |
Type |
Journal |
|
Year |
2014 |
Publication |
Manuscript Cultures |
Abbreviated Journal |
|
|
|
Volume |
7 |
Issue |
|
Pages |
47-58 |
|
|
Keywords |
|
|
|
Abstract |
With the ongoing progress in digitization, huge document collections and archives have become available to a broad audience. Scanned document images can be transmitted electronically and studied simultaneously throughout the world. While this is very beneficial, it is often impossible to perform automated searches on these document collections. Optical character recognition usually fails when it comes to handwritten or historic documents. In order to address the need for exploring document collections rapidly, researchers are working on word spotting. In query-by-example word spotting scenarios, the user selects an exemplary occurrence of the query word in a document image. The word spotting system then retrieves all regions in the collection that are visually similar to the given example of the query word. The best matching regions are presented to the user and no actual transcription is required.
An important property of a word spotting system is the computational speed with which queries can be executed. In our previous work, we presented a relatively slow but high-precision method. In the present work, we will extend this baseline system to an integrated two-stage approach. In a coarse-grained first stage, we will filter document images efficiently in order to identify regions that are likely to contain the query word. In the fine-grained second stage, these regions will be analyzed with our previously presented high-precision method. Finally, we will report recognition results and query times for the well-known George Washington
benchmark in our evaluation. We achieve state-of-the-art recognition results while the query times can be reduced to 50% in comparison with our baseline. |
|
|
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; 600.061; 600.077 |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
3190 |
|
Permanent link to this record |