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Author | Anders Hast; Alicia Fornes | ||||
Title | A Segmentation-free Handwritten Word Spotting Approach by Relaxed Feature Matching | Type | Conference Article | ||
Year | 2016 | Publication | 12th IAPR Workshop on Document Analysis Systems | Abbreviated Journal | |
Volume | Issue | Pages | 150-155 | ||
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Abstract | The automatic recognition of historical handwritten documents is still considered challenging task. For this reason, word spotting emerges as a good alternative for making the information contained in these documents available to the user. Word spotting is defined as the task of retrieving all instances of the query word in a document collection, becoming a useful tool for information retrieval. In this paper we propose a segmentation-free word spotting approach able to deal with large document collections. Our method is inspired on feature matching algorithms that have been applied to image matching and retrieval. Since handwritten words have different shape, there is no exact transformation to be obtained. However, the sufficient degree of relaxation is achieved by using a Fourier based descriptor and an alternative approach to RANSAC called PUMA. The proposed approach is evaluated on historical marriage records, achieving promising results. | ||||
Address | Santorini; Greece; April 2016 | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | DAS | ||
Notes | DAG; 602.006; 600.061; 600.077; 600.097 | Approved | no | ||
Call Number | HaF2016 | Serial | 2753 | ||
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Author | Dimosthenis Karatzas; V. Poulain d'Andecy; Marçal Rusiñol | ||||
Title | Human-Document Interaction – a new frontier for document image analysis | Type | Conference Article | ||
Year | 2016 | Publication | 12th IAPR Workshop on Document Analysis Systems | Abbreviated Journal | |
Volume | Issue | Pages | 369-374 | ||
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Abstract | All indications show that paper documents will not cede in favour of their digital counterparts, but will instead be used increasingly in conjunction with digital information. An open challenge is how to seamlessly link the physical with the digital – how to continue taking advantage of the important affordances of paper, without missing out on digital functionality. This paper
presents the authors’ experience with developing systems for Human-Document Interaction based on augmented document interfaces and examines new challenges and opportunities arising for the document image analysis field in this area. The system presented combines state of the art camera-based document image analysis techniques with a range of complementary tech-nologies to offer fluid Human-Document Interaction. Both fixed and nomadic setups are discussed that have gone through user testing in real-life environments, and use cases are presented that span the spectrum from business to educational application |
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Address | Santorini; Greece; April 2016 | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | DAS | ||
Notes | DAG; 600.084; 600.077 | Approved | no | ||
Call Number | KPR2016 | Serial | 2756 | ||
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Author | Q. Bao; Marçal Rusiñol; M.Coustaty; Muhammad Muzzamil Luqman; C.D. Tran; Jean-Marc Ogier | ||||
Title | Delaunay triangulation-based features for Camera-based document image retrieval system | Type | Conference Article | ||
Year | 2016 | Publication | 12th IAPR Workshop on Document Analysis Systems | Abbreviated Journal | |
Volume | Issue | Pages | 1-6 | ||
Keywords | Camera-based Document Image Retrieval; Delaunay Triangulation; Feature descriptors; Indexing | ||||
Abstract | In this paper, we propose a new feature vector, named DElaunay TRIangulation-based Features (DETRIF), for real-time camera-based document image retrieval. DETRIF is computed based on the geometrical constraints from each pair of adjacency triangles in delaunay triangulation which is constructed from centroids of connected components. Besides, we employ a hashing-based indexing system in order to evaluate the performance of DETRIF and to compare it with other systems such as LLAH and SRIF. The experimentation is carried out on two datasets comprising of 400 heterogeneous-content complex linguistic map images (huge size, 9800 X 11768 pixels resolution)and 700 textual document images. | ||||
Address | Santorini; Greece; April 2016 | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | DAS | ||
Notes | DAG; 600.061; 600.084; 600.077 | Approved | no | ||
Call Number | Admin @ si @ BRC2016 | Serial | 2757 | ||
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Author | Lluis Gomez; Dimosthenis Karatzas | ||||
Title | A fine-grained approach to scene text script identification | Type | Conference Article | ||
Year | 2016 | Publication | 12th IAPR Workshop on Document Analysis Systems | Abbreviated Journal | |
Volume | Issue | Pages | 192-197 | ||
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Abstract | This paper focuses on the problem of script identification in unconstrained scenarios. Script identification is an important prerequisite to recognition, and an indispensable condition for automatic text understanding systems designed for multi-language environments. Although widely studied for document images and handwritten documents, it remains an almost unexplored territory for scene text images. We detail a novel method for script identification in natural images that combines convolutional features and the Naive-Bayes Nearest Neighbor classifier. The proposed framework efficiently exploits the discriminative power of small stroke-parts, in a fine-grained classification framework. In addition, we propose a new public benchmark dataset for the evaluation of joint text detection and script identification in natural scenes. Experiments done in this new dataset demonstrate that the proposed method yields state of the art results, while it generalizes well to different datasets and variable number of scripts. The evidence provided shows that multi-lingual scene text recognition in the wild is a viable proposition. Source code of the proposed method is made available online. | ||||
Address | Santorini; Grecia; April 2016 | ||||
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Area | Expedition | Conference | DAS | ||
Notes | DAG; 601.197; 600.084 | Approved | no | ||
Call Number | Admin @ si @ GoK2016b | Serial | 2863 | ||
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Author | Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero | ||||
Title | Banknote counterfeit detection through background texture printing analysis | Type | Conference Article | ||
Year | 2016 | Publication | 12th IAPR Workshop on Document Analysis Systems | Abbreviated Journal | |
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Abstract | This paper is focused on the detection of counterfeit photocopy banknotes. The main difficulty is to work on a real industrial scenario without any constraint about the acquisition device and with a single image. The main contributions of this paper are twofold: first the adaptation and performance evaluation of existing approaches to classify the genuine and photocopy banknotes using background texture printing analysis, which have not been applied into this context before. Second, a new dataset of Euro banknotes images acquired with several cameras under different luminance conditions to evaluate these methods. Experiments on the proposed algorithms show that mixing SIFT features and sparse coding dictionaries achieves quasi perfect classification using a linear SVM with the created dataset. Approaches using dictionaries to cover all possible texture variations have demonstrated to be robust and outperform the state-of-the-art methods using the proposed benchmark. | ||||
Address | Rumania; May 2016 | ||||
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Area | Expedition | Conference | DAS | ||
Notes | DAG; 600.061; 601.269; 600.097 | Approved | no | ||
Call Number | Admin @ si @ BRL2016 | Serial | 2950 | ||
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Author | Oriol Vicente; Alicia Fornes; Ramon Valdes | ||||
Title | The Digital Humanities Network of the UABCie: a smart structure of research and social transference for the digital humanities | Type | Conference Article | ||
Year | 2016 | Publication | Digital Humanities Centres: Experiences and Perspectives | Abbreviated Journal | |
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Address | Warsaw; Poland; December 2016 | ||||
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Area | Expedition | Conference | DHLABS | ||
Notes | DAG; 600.097 | Approved | no | ||
Call Number | Admin @ si @ VFV2016 | Serial | 2908 | ||
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Author | Fernando Vilariño; Dan Norton; Onur Ferhat | ||||
Title | The Eye Doesn't Click – Eyetracking and Digital Content Interaction | Type | Conference Article | ||
Year | 2016 | Publication | 4S/EASST Conference | Abbreviated Journal | |
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Address | Barcelona; Spain; September 2016 | ||||
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Area | Expedition | Conference | EASST | ||
Notes | MV; 600.097;SIAI | Approved | no | ||
Call Number | Admin @ si @VNF2016 | Serial | 2801 | ||
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Author | Cesar de Souza; Adrien Gaidon; Eleonora Vig; Antonio Lopez | ||||
Title | Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition | Type | Conference Article | ||
Year | 2016 | Publication | 14th European Conference on Computer Vision | Abbreviated Journal | |
Volume | Issue | Pages | 697-716 | ||
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Abstract | Action recognition in videos is a challenging task due to the complexity of the spatio-temporal patterns to model and the difficulty to acquire and learn on large quantities of video data. Deep learning, although a breakthrough for image classification and showing promise for videos, has still not clearly superseded action recognition methods using hand-crafted features, even when training on massive datasets. In this paper, we introduce hybrid video classification architectures based on carefully designed unsupervised representations of hand-crafted spatio-temporal features classified by supervised deep networks. As we show in our experiments on five popular benchmarks for action recognition, our hybrid model combines the best of both worlds: it is data efficient (trained on 150 to 10000 short clips) and yet improves significantly on the state of the art, including recent deep models trained on millions of manually labelled images and videos. | ||||
Address | Amsterdam; The Netherlands; October 2016 | ||||
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ECCV | ||
Notes | ADAS; 600.076; 600.085 | Approved | no | ||
Call Number | Admin @ si @ SGV2016 | Serial | 2824 | ||
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Author | Y. Patel; Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas | ||||
Title | Dynamic Lexicon Generation for Natural Scene Images | Type | Conference Article | ||
Year | 2016 | Publication | 14th European Conference on Computer Vision Workshops | Abbreviated Journal | |
Volume | Issue | Pages | 395-410 | ||
Keywords | scene text; photo OCR; scene understanding; lexicon generation; topic modeling; CNN | ||||
Abstract | Many scene text understanding methods approach the endtoend recognition problem from a word-spotting perspective and take huge benet from using small per-image lexicons. Such customized lexicons are normally assumed as given and their source is rarely discussed.
In this paper we propose a method that generates contextualized lexicons for scene images using only visual information. For this, we exploit the correlation between visual and textual information in a dataset consisting of images and textual content associated with them. Using the topic modeling framework to discover a set of latent topics in such a dataset allows us to re-rank a xed dictionary in a way that prioritizes the words that are more likely to appear in a given image. Moreover, we train a CNN that is able to reproduce those word rankings but using only the image raw pixels as input. We demonstrate that the quality of the automatically obtained custom lexicons is superior to a generic frequency-based baseline. |
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Address | Amsterdam; The Netherlands; October 2016 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ECCVW | ||
Notes | DAG; 600.084 | Approved | no | ||
Call Number | Admin @ si @ PGR2016 | Serial | 2825 | ||
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Author | Victor Ponce; Baiyu Chen; Marc Oliu; Ciprian Corneanu; Albert Clapes; Isabelle Guyon; Xavier Baro; Hugo Jair Escalante; Sergio Escalera | ||||
Title | ChaLearn LAP 2016: First Round Challenge on First Impressions – Dataset and Results | Type | Conference Article | ||
Year | 2016 | Publication | 14th European Conference on Computer Vision Workshops | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Behavior Analysis; Personality Traits; First Impressions | ||||
Abstract | This paper summarizes the ChaLearn Looking at People 2016 First Impressions challenge data and results obtained by the teams in the rst round of the competition. The goal of the competition was to automatically evaluate ve \apparent“ personality traits (the so-called \Big Five”) from videos of subjects speaking in front of a camera, by using human judgment. In this edition of the ChaLearn challenge, a novel data set consisting of 10,000 shorts clips from YouTube videos has been made publicly available. The ground truth for personality traits was obtained from workers of Amazon Mechanical Turk (AMT). To alleviate calibration problems between workers, we used pairwise comparisons between videos, and variable levels were reconstructed by tting a Bradley-Terry-Luce model with maximum likelihood. The CodaLab open source
platform was used for submission of predictions and scoring. The competition attracted, over a period of 2 months, 84 participants who are grouped in several teams. Nine teams entered the nal phase. Despite the diculty of the task, the teams made great advances in this round of the challenge. |
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Address | Amsterdam; The Netherlands; October 2016 | ||||
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Area | Expedition | Conference | ECCVW | ||
Notes | HuPBA;MV; 600.063 | Approved | no | ||
Call Number | Admin @ si @ PCP2016 | Serial | 2828 | ||
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Author | Baiyu Chen; Sergio Escalera; Isabelle Guyon; Victor Ponce; N. Shah; Marc Oliu | ||||
Title | Overcoming Calibration Problems in Pattern Labeling with Pairwise Ratings: Application to Personality Traits | Type | Conference Article | ||
Year | 2016 | Publication | 14th European Conference on Computer Vision Workshops | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Calibration of labels; Label bias; Ordinal labeling; Variance Models; Bradley-Terry-Luce model; Continuous labels; Regression; Personality traits; Crowd-sourced labels | ||||
Abstract | We address the problem of calibration of workers whose task is to label patterns with continuous variables, which arises for instance in labeling images of videos of humans with continuous traits. Worker bias is particularly dicult to evaluate and correct when many workers contribute just a few labels, a situation arising typically when labeling is crowd-sourced. In the scenario of labeling short videos of people facing a camera with personality traits, we evaluate the feasibility of the pairwise ranking method to alleviate bias problems. Workers are exposed to pairs of videos at a time and must order by preference. The variable levels are reconstructed by fitting a Bradley-Terry-Luce model with maximum likelihood. This method may at first sight, seem prohibitively expensive because for N videos, p = N (N-1)/2 pairs must be potentially processed by workers rather that N videos. However, by performing extensive simulations, we determine an empirical law for the scaling of the number of pairs needed as a function of the number of videos in order to achieve a given accuracy of score reconstruction and show that the pairwise method is a ordable. We apply the method to the labeling of a large scale dataset of 10,000 videos used in the ChaLearn Apparent Personality Trait challenge. | ||||
Address | Amsterdam; The Netherlands; October 2016 | ||||
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Area | Expedition | Conference | ECCVW | ||
Notes | HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ CEG2016 | Serial | 2829 | ||
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Author | Iiris Lusi; Sergio Escalera; Gholamreza Anbarjafari | ||||
Title | SASE: RGB-Depth Database for Human Head Pose Estimation | Type | Conference Article | ||
Year | 2016 | Publication | 14th European Conference on Computer Vision Workshops | Abbreviated Journal | |
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Abstract | Slides | ||||
Address | Amsterdam; The Netherlands; October 2016 | ||||
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Area | Expedition | Conference | ECCVW | ||
Notes | HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ LEA2016a | Serial | 2840 | ||
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Author | Saad Minhas; Aura Hernandez-Sabate; Shoaib Ehsan; Katerine Diaz; Ales Leonardis; Antonio Lopez; Klaus McDonald Maier | ||||
Title | LEE: A photorealistic Virtual Environment for Assessing Driver-Vehicle Interactions in Self-Driving Mode | Type | Conference Article | ||
Year | 2016 | Publication | 14th European Conference on Computer Vision Workshops | Abbreviated Journal | |
Volume | 9915 | Issue | Pages | 894-900 | |
Keywords | Simulation environment; Automated Driving; Driver-Vehicle interaction | ||||
Abstract | Photorealistic virtual environments are crucial for developing and testing automated driving systems in a safe way during trials. As commercially available simulators are expensive and bulky, this paper presents a low-cost, extendable, and easy-to-use (LEE) virtual environment with the aim to highlight its utility for level 3 driving automation. In particular, an experiment is performed using the presented simulator to explore the influence of different variables regarding control transfer of the car after the system was driving autonomously in a highway scenario. The results show that the speed of the car at the time when the system needs to transfer the control to the human driver is critical. | ||||
Address | Amsterdam; The Netherlands; October 2016 | ||||
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Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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Area | Expedition | Conference | ECCVW | ||
Notes | ADAS;IAM; 600.085; 600.076 | Approved | no | ||
Call Number | MHE2016 | Serial | 2865 | ||
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Author | Fernando Vilariño; Dimosthenis Karatzas | ||||
Title | A Living Lab approach for Citizen Science in Libraries | Type | Conference Article | ||
Year | 2016 | Publication | 1st International ECSA Conference | Abbreviated Journal | |
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Address | Berlin; Germany; May 2016 | ||||
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Area | Expedition | Conference | ECSA | ||
Notes | MV; DAG; 600.084; 600.097;SIAI | Approved | no | ||
Call Number | Admin @ si @ViK2016 | Serial | 2804 | ||
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Author | Ivet Rafegas; Maria Vanrell | ||||
Title | Colour Visual Coding in trained Deep Neural Networks | Type | Abstract | ||
Year | 2016 | Publication | European Conference on Visual Perception | Abbreviated Journal | |
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Address | Barcelona; Spain; August 2016 | ||||
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Area | Expedition | Conference | ECVP | ||
Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ RaV2016b | Serial | 2895 | ||
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