|
Records |
Links |
|
Author |
Daniel Sanchez; Meysam Madadi; Marc Oliu; Sergio Escalera |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Multi-task human analysis in still images: 2D/3D pose, depth map, and multi-part segmentation |
Type |
Conference Article |
|
Year |
2019 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th IEEE International Conference on Automatic Face and Gesture Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
While many individual tasks in the domain of human analysis have recently received an accuracy boost from deep learning approaches, multi-task learning has mostly been ignored due to a lack of data. New synthetic datasets are being released, filling this gap with synthetic generated data. In this work, we analyze four related human analysis tasks in still images in a multi-task scenario by leveraging such datasets. Specifically, we study the correlation of 2D/3D pose estimation, body part segmentation and full-body depth estimation. These tasks are learned via the well-known Stacked Hourglass module such that each of the task-specific streams shares information with the others. The main goal is to analyze how training together these four related tasks can benefit each individual task for a better generalization. Results on the newly released SURREAL dataset show that all four tasks benefit from the multi-task approach, but with different combinations of tasks: while combining all four tasks improves 2D pose estimation the most, 2D pose improves neither 3D pose nor full-body depth estimation. On the other hand 2D parts segmentation can benefit from 2D pose but not from 3D pose. In all cases, as expected, the maximum improvement is achieved on those human body parts that show more variability in terms of spatial distribution, appearance and shape, e.g. wrists and ankles. |
|
|
Address |
Lille; France; May 2019 |
|
|
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 |
FG |
|
|
Notes |
HUPBA; no proj |
Approved |
no |
|
|
Call Number |
Admin @ si @ SMO2019 |
Serial |
3326 |
|
Permanent link to this record |
|
|
|
|
Author |
H. Emrah Tasli; Cevahir Çigla; Theo Gevers; A. Aydin Alatan |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Super pixel extraction via convexity induced boundary adaptation |
Type |
Conference Article |
|
Year |
2013 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th IEEE International Conference on Multimedia and Expo |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1-6 |
|
|
Keywords |
|
|
|
Abstract |
This study presents an efficient super-pixel extraction algorithm with major contributions to the state-of-the-art in terms of accuracy and computational complexity. Segmentation accuracy is improved through convexity constrained geodesic distance utilization; while computational efficiency is achieved by replacing complete region processing with boundary adaptation idea. Starting from the uniformly distributed rectangular equal-sized super-pixels, region boundaries are adapted to intensity edges iteratively by assigning boundary pixels to the most similar neighboring super-pixels. At each iteration, super-pixel regions are updated and hence progressively converging to compact pixel groups. Experimental results with state-of-the-art comparisons, validate the performance of the proposed technique in terms of both accuracy and speed. |
|
|
Address |
San Jose; USA; July 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 |
1945-7871 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICME |
|
|
Notes |
ALTRES;ISE |
Approved |
no |
|
|
Call Number |
Admin @ si @ TÇG2013 |
Serial |
2367 |
|
Permanent link to this record |
|
|
|
|
Author |
Xavier Soria; Angel Sappa |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Improving Edge Detection in RGB Images by Adding NIR Channel |
Type |
Conference Article |
|
Year |
2018 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th IEEE International Conference on Signal Image Technology & Internet Based System |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
Edge detection; Contour detection; VGG; CNN; RGB-NIR; Near infrared images |
|
|
Abstract |
The edge detection is yet a critical problem in many computer vision and image processing tasks. The manuscript presents an Holistically-Nested Edge Detection based approach to study the inclusion of Near-Infrared in the Visible spectrum
images. To do so, a Single Sensor based dataset has been acquired in the range of 400nm to 1100nm wavelength spectral band. Prominent results have been obtained even when the ground truth (annotated edge-map) is based in the visible wavelength spectrum. |
|
|
Address |
Las Palmas de Gran Canaria; November 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 |
SITIS |
|
|
Notes |
MSIAU; 600.122 |
Approved |
no |
|
|
Call Number |
Admin @ si @ SoS2018 |
Serial |
3192 |
|
Permanent link to this record |
|
|
|
|
Author |
Patricia Suarez; Angel Sappa; Boris X. Vintimilla |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Cross-spectral image dehaze through a dense stacked conditional GAN based approach |
Type |
Conference Article |
|
Year |
2018 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th IEEE International Conference on Signal Image Technology & Internet Based System |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
Infrared imaging; Dense; Stacked CGAN; Crossspectral; Convolutional networks |
|
|
Abstract |
This paper proposes a novel approach to remove haze from RGB images using a near infrared images based on a dense stacked conditional Generative Adversarial Network (CGAN). The architecture of the deep network implemented
receives, besides the images with haze, its corresponding image in the near infrared spectrum, which serve to accelerate the learning process of the details of the characteristics of the images. The model uses a triplet layer that allows the independence learning of each channel of the visible spectrum image to remove the haze on each color channel separately. A multiple loss function scheme is proposed, which ensures balanced learning between the colors
and the structure of the images. Experimental results have shown that the proposed method effectively removes the haze from the images. Additionally, the proposed approach is compared with a state of the art approach showing better results. |
|
|
Address |
Las Palmas de Gran Canaria; November 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 |
978-1-5386-9385-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
SITIS |
|
|
Notes |
MSIAU; 600.086; 600.130; 600.122 |
Approved |
no |
|
|
Call Number |
Admin @ si @ SSV2018a |
Serial |
3193 |
|
Permanent link to this record |
|
|
|
|
Author |
Jorge Charco; Boris X. Vintimilla; Angel Sappa |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Deep learning based camera pose estimation in multi-view environment |
Type |
Conference Article |
|
Year |
2018 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th IEEE International Conference on Signal Image Technology & Internet Based System |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
Deep learning; Camera pose estimation; Multiview environment; Siamese architecture |
|
|
Abstract |
This paper proposes to use a deep learning network architecture for relative camera pose estimation on a multi-view environment. The proposed network is a variant architecture of AlexNet to use as regressor for prediction the relative translation and rotation as output. The proposed approach is trained from
scratch on a large data set that takes as input a pair of imagesfrom the same scene. This new architecture is compared with a previous approach using standard metrics, obtaining better results on the relative camera pose. |
|
|
Address |
Las Palmas de Gran Canaria; November 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 |
SITIS |
|
|
Notes |
MSIAU; 600.086; 600.130; 600.122 |
Approved |
no |
|
|
Call Number |
Admin @ si @ CVS2018 |
Serial |
3194 |
|
Permanent link to this record |
|
|
|
|
Author |
Muhammad Anwer Rao; David Vazquez; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
Type |
Conference Article |
|
Year |
2011 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
|
|
|
Volume |
6855 |
Issue |
II |
Pages |
463-470 |
|
|
Keywords |
Pedestrian Detection; Color |
|
|
Abstract |
Camera-based person detection is of paramount interest due to its potential applications. The task is diffcult because the great variety of backgrounds (scenarios, illumination) in which persons are present, as well as their intra-class variability (pose, clothe, occlusion). In fact, the class person is one of the included in the popular PASCAL visual object classes (VOC) challenge. A breakthrough for this challenge, regarding person detection, is due to Felzenszwalb et al. These authors proposed a part-based detector that relies on histograms of oriented gradients (HOG) and latent support vector machines (LatSVM) to learn a model of the whole human body and its constitutive parts, as well as their relative position. Since the approach of Felzenszwalb et al. appeared new variants have been proposed, usually giving rise to more complex models. In this paper, we focus on an issue that has not attracted suficient interest up to now. In particular, we refer to the fact that HOG is usually computed from RGB color space, but other possibilities exist and deserve the corresponding investigation. In this paper we challenge RGB space with the opponent color space (OPP), which is inspired in the human vision system.We will compute the HOG on top of OPP, then we train and test the part-based human classifer by Felzenszwalb et al. using PASCAL VOC challenge protocols and person database. Our experiments demonstrate that OPP outperforms RGB. We also investigate possible differences among types of scenarios: indoor, urban and countryside. Interestingly, our experiments suggest that the beneficts of OPP with respect to RGB mainly come for indoor and countryside scenarios, those in which the human visual system was designed by evolution. |
|
|
Address |
Seville, Spain |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
Berlin Heidelberg |
Editor |
P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
|
|
Language |
English |
Summary Language |
english |
Original Title |
Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-23677-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CAIP |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ RVL2011b |
Serial |
1665 |
|
Permanent link to this record |
|
|
|
|
Author |
Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Inferring the Performance of Medical Imaging Algorithms |
Type |
Conference Article |
|
Year |
2011 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
|
|
|
Volume |
6854 |
Issue |
|
Pages |
520-528 |
|
|
Keywords |
Validation, Statistical Inference, Medical Imaging Algorithms. |
|
|
Abstract |
Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence. |
|
|
Address |
Sevilla |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer-Verlag Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
L |
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CAIP |
|
|
Notes |
IAM; ADAS |
Approved |
no |
|
|
Call Number |
IAM @ iam @ HGR2011 |
Serial |
1676 |
|
Permanent link to this record |
|
|
|
|
Author |
Naveen Onkarappa; Angel Sappa |
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Space Variant Representations for Mobile Platform Vision Applications |
Type |
Conference Article |
|
Year |
2011 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
|
|
|
Volume |
6855 |
Issue |
II |
Pages |
146-154 |
|
|
Keywords |
|
|
|
Abstract |
The log-polar space variant representation, motivated by biological vision, has been widely studied in the literature. Its data reduction and invariance properties made it useful in many vision applications. However, due to its nature, it fails in preserving features in the periphery. In the current work, as an attempt to overcome this problem, we propose a novel space-variant representation. It is evaluated and proved to be better than the log-polar representation in preserving the peripheral information, crucial for on-board mobile vision applications. The evaluation is performed by comparing log-polar and the proposed representation once they are used for estimating dense optical flow. |
|
|
Address |
Seville, Spain |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-23677-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CAIP |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
NaS2011; ADAS @ adas @ |
Serial |
1686 |
|
Permanent link to this record |
|
|
|
|
Author |
Chris Bahnsen; David Vazquez; Antonio Lopez; Thomas B. Moeslund |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Learning to Remove Rain in Traffic Surveillance by Using Synthetic Data |
Type |
Conference Article |
|
Year |
2019 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
123-130 |
|
|
Keywords |
Rain Removal; Traffic Surveillance; Image Denoising |
|
|
Abstract |
Rainfall is a problem in automated traffic surveillance. Rain streaks occlude the road users and degrade the overall visibility which in turn decrease object detection performance. One way of alleviating this is by artificially removing the rain from the images. This requires knowledge of corresponding rainy and rain-free images. Such images are often produced by overlaying synthetic rain on top of rain-free images. However, this method fails to incorporate the fact that rain fall in the entire three-dimensional volume of the scene. To overcome this, we introduce training data from the SYNTHIA virtual world that models rain streaks in the entirety of a scene. We train a conditional Generative Adversarial Network for rain removal and apply it on traffic surveillance images from SYNTHIA and the AAU RainSnow datasets. To measure the applicability of the rain-removed images in a traffic surveillance context, we run the YOLOv2 object detection algorithm on the original and rain-removed frames. The results on SYNTHIA show an 8% increase in detection accuracy compared to the original rain image. Interestingly, we find that high PSNR or SSIM scores do not imply good object detection performance. |
|
|
Address |
Praga; Czech Republic; February 2019 |
|
|
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 |
VISIGRAPP |
|
|
Notes |
ADAS; 600.118 |
Approved |
no |
|
|
Call Number |
Admin @ si @ BVL2019 |
Serial |
3256 |
|
Permanent link to this record |
|
|
|
|
Author |
Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
LSDE: Levenshtein Space Deep Embedding for Query-by-string Word Spotting |
Type |
Conference Article |
|
Year |
2017 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
n this paper we present the LSDE string representation and its application to handwritten word spotting. LSDE is a novel embedding approach for representing strings that learns a space in which distances between projected points are correlated with the Levenshtein edit distance between the original strings.
We show how such a representation produces a more semantically interpretable retrieval from the user’s perspective than other state of the art ones such as PHOC and DCToW. We also conduct a preliminary handwritten word spotting experiment on the George Washington dataset. |
|
|
Address |
Kyoto; Japan; November 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 |
ICDAR |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GRK2017 |
Serial |
2999 |
|
Permanent link to this record |
|
|
|
|
Author |
E. Royer; J. Chazalon; Marçal Rusiñol; F. Bouchara |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Benchmarking Keypoint Filtering Approaches for Document Image Matching |
Type |
Conference Article |
|
Year |
2017 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Best Poster Award.
Reducing the amount of keypoints used to index an image is particularly interesting to control processing time and memory usage in real-time document image matching applications, like augmented documents or smartphone applications. This paper benchmarks two keypoint selection methods on a task consisting of reducing keypoint sets extracted from document images, while preserving detection and segmentation accuracy. We first study the different forms of keypoint filtering, and we introduce the use of the CORE selection method on
keypoints extracted from document images. Then, we extend a previously published benchmark by including evaluations of the new method, by adding the SURF-BRISK detection/description scheme, and by reporting processing speeds. Evaluations are conducted on the publicly available dataset of ICDAR2015 SmartDOC challenge 1. Finally, we prove that reducing the original keypoint set is always feasible and can be beneficial
not only to processing speed but also to accuracy. |
|
|
Address |
Kyoto; Japan; November 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 |
ICDAR |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RCR2017 |
Serial |
3000 |
|
Permanent link to this record |
|
|
|
|
Author |
David Aldavert; Marçal Rusiñol; Ricardo Toledo |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Automatic Static/Variable Content Separation in Administrative Document Images |
Type |
Conference Article |
|
Year |
2017 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
In this paper we present an automatic method for separating static and variable content from administrative document images. An alignment approach is able to unsupervisedly build probabilistic templates from a set of examples of the same document kind. Such templates define which is the likelihood of every pixel of being either static or variable content. In the extraction step, the same alignment technique is used to match
an incoming image with the template and to locate the positions where variable fields appear. We validate our approach on the public NIST Structured Tax Forms Dataset. |
|
|
Address |
Kyoto; Japan; November 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 |
ICDAR |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ ART2017 |
Serial |
3001 |
|
Permanent link to this record |
|
|
|
|
Author |
N. Nayef; F. Yin; I. Bizid; H .Choi; Y. Feng; Dimosthenis Karatzas; Z. Luo; Umapada Pal; Christophe Rigaud; J. Chazalon; W. Khlif; Muhammad Muzzamil Luqman; Jean-Christophe Burie; C.L. Liu; Jean-Marc Ogier |
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
ICDAR2017 Robust Reading Challenge on Multi-Lingual Scene Text Detection and Script Identification – RRC-MLT |
Type |
Conference Article |
|
Year |
2017 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1454-1459 |
|
|
Keywords |
|
|
|
Abstract |
Text detection and recognition in a natural environment are key components of many applications, ranging from business card digitization to shop indexation in a street. This competition aims at assessing the ability of state-of-the-art methods to detect Multi-Lingual Text (MLT) in scene images, such as in contents gathered from the Internet media and in modern cities where multiple cultures live and communicate together. This competition is an extension of the Robust Reading Competition (RRC) which has been held since 2003 both in ICDAR and in an online context. The proposed competition is presented as a new challenge of the RRC. The dataset built for this challenge largely extends the previous RRC editions in many aspects: the multi-lingual text, the size of the dataset, the multi-oriented text, the wide variety of scenes. The dataset is comprised of 18,000 images which contain text belonging to 9 languages. The challenge is comprised of three tasks related to text detection and script classification. We have received a total of 16 participations from the research and industrial communities. This paper presents the dataset, the tasks and the findings of this RRC-MLT challenge. |
|
|
Address |
Kyoto; Japan; November 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 |
978-1-5386-3586-5 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ NYB2017 |
Serial |
3097 |
|
Permanent link to this record |
|
|
|
|
Author |
Alicia Fornes; Veronica Romero; Arnau Baro; Juan Ignacio Toledo; Joan Andreu Sanchez; Enrique Vidal; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
ICDAR2017 Competition on Information Extraction in Historical Handwritten Records |
Type |
Conference Article |
|
Year |
2017 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1389-1394 |
|
|
Keywords |
|
|
|
Abstract |
The extraction of relevant information from historical handwritten document collections is one of the key steps in order to make these manuscripts available for access and searches. In this competition, the goal is to detect the named entities and assign each of them a semantic category, and therefore, to simulate the filling in of a knowledge database. This paper describes the dataset, the tasks, the evaluation metrics, the participants methods and the results. |
|
|
Address |
Kyoto; Japan; November 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 |
ICDAR |
|
|
Notes |
DAG; 600.097; 601.225; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ FRB2017 |
Serial |
3052 |
|
Permanent link to this record |
|
|
|
|
Author |
Pau Riba; Anjan Dutta; Josep Llados; Alicia Fornes; Sounak Dey |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Improving Information Retrieval in Multiwriter Scenario by Exploiting the Similarity Graph of Document Terms |
Type |
Conference Article |
|
Year |
2017 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
475-480 |
|
|
Keywords |
document terms; information retrieval; affinity graph; graph of document terms; multiwriter; graph diffusion |
|
|
Abstract |
Information Retrieval (IR) is the activity of obtaining information resources relevant to a questioned information. It usually retrieves a set of objects ranked according to the relevancy to the needed fact. In document analysis, information retrieval receives a lot of attention in terms of symbol and word spotting. However, through decades the community mostly focused either on printed or on single writer scenario, where the
state-of-the-art results have achieved reasonable performance on the available datasets. Nevertheless, the existing algorithms do not perform accordingly on multiwriter scenario. A graph representing relations between a set of objects is a structure where each node delineates an individual element and the similarity between them is represented as a weight on the connecting edge. In this paper, we explore different analytics of graphs constructed from words or graphical symbols, such as diffusion, shortest path, etc. to improve the performance of information retrieval methods in multiwriter scenario |
|
|
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 |
ICDAR |
|
|
Notes |
DAG; 600.097; 601.302; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RDL2017a |
Serial |
3053 |
|
Permanent link to this record |