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Author Francisco Cruz; Oriol Ramos Terrades
Title Handwritten Line Detection via an EM Algorithm Type Conference Article
Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 718-722
Keywords
Abstract In this paper we present a handwritten line segmentation method devised to work on documents composed of several paragraphs with multiple line orientations. The method is based on a variation of the EM algorithm for the estimation of a set of regression lines between the connected components that compose the image. We evaluated our method on the ICDAR2009 handwriting segmentation contest dataset with promising results that overcome most of the presented methods. In addition, we prove the usability of the presented method by performing line segmentation on the George Washington database obtaining encouraging results.
Address Washington; 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 1520-5363 ISBN Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number Admin @ si @ CrT2013 Serial (down) 2329
Permanent link to this record
 
 
Author Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Bemedi
Title Page Segmentation of Structured Documents Using 2D Stochastic Context-Free Grammars Type Conference Article
Year 2013 Publication 6th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 7887 Issue Pages 133-140
Keywords
Abstract In this paper we define a bidimensional extension of Stochastic Context-Free Grammars for page segmentation of structured documents. Two sets of text classification features are used to perform an initial classification of each zone of the page. Then, the page segmentation is obtained as the most likely hypothesis according to a grammar. This approach is compared to Conditional Random Fields and results show significant improvements in several cases. Furthermore, grammars provide a detailed segmentation that allowed a semantic evaluation which also validates this model.
Address Madeira; Portugal; June 2013
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-38627-5 Medium
Area Expedition Conference IbPRIA
Notes DAG; 605.203 Approved no
Call Number Admin @ si @ ACS2013 Serial (down) 2328
Permanent link to this record
 
 
Author Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny
Title Handwritten Word Spotting with Corrected Attributes Type Conference Article
Year 2013 Publication 15th IEEE International Conference on Computer Vision Abbreviated Journal
Volume Issue Pages 1017-1024
Keywords
Abstract We propose an approach to multi-writer word spotting, where the goal is to find a query word in a dataset comprised of document images. We propose an attributes-based approach that leads to a low-dimensional, fixed-length representation of the word images that is fast to compute and, especially, fast to compare. This approach naturally leads to an unified representation of word images and strings, which seamlessly allows one to indistinctly perform query-by-example, where the query is an image, and query-by-string, where the query is a string. We also propose a calibration scheme to correct the attributes scores based on Canonical Correlation Analysis that greatly improves the results on a challenging dataset. We test our approach on two public datasets showing state-of-the-art results.
Address Sydney; Australia; December 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 1550-5499 ISBN Medium
Area Expedition Conference ICCV
Notes DAG Approved no
Call Number Admin @ si @ AGF2013 Serial (down) 2327
Permanent link to this record
 
 
Author Jon Almazan; Alicia Fornes; Ernest Valveny
Title A Deformable HOG-based Shape Descriptor Type Conference Article
Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 1022-1026
Keywords
Abstract In this paper we deal with the problem of recognizing handwritten shapes. We present a new deformable feature extraction method that adapts to the shape to be described, dealing in this way with the variability introduced in the handwriting domain. It consists in a selection of the regions that best define the shape to be described, followed by the computation of histograms of oriented gradients-based features over these points. Our results significantly outperform other descriptors in the literature for the task of hand-drawn shape recognition and handwritten word retrieval
Address Washington; 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 1520-5363 ISBN Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number Admin @ si @ AFV2013 Serial (down) 2326
Permanent link to this record
 
 
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
Volume 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
Corporate Author Thesis
Publisher Springer Briefs in Computer Vision Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-4614-7986-4 Medium
Area Expedition Conference
Notes ADAS; 600.076 Approved no
Call Number GeL2014 Serial (down) 2325
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Author Alvaro Cepero; Albert Clapes; Sergio Escalera
Title Quantitative analysis of non-verbal communication for competence analysis Type Conference Article
Year 2013 Publication 16th Catalan Conference on Artificial Intelligence Abbreviated Journal
Volume 256 Issue Pages 105-114
Keywords
Abstract
Address Vic; October 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 CCIA
Notes HUPBA;MILAB Approved no
Call Number Admin @ si @ CCE2013 Serial (down) 2324
Permanent link to this record
 
 
Author Vitaliy Konovalov; Albert Clapes; Sergio Escalera
Title Automatic Hand Detection in RGB-Depth Data Sequences Type Conference Article
Year 2013 Publication 16th Catalan Conference on Artificial Intelligence Abbreviated Journal
Volume Issue Pages 91-100
Keywords
Abstract Detecting hands in multi-modal RGB-Depth visual data has become a challenging Computer Vision problem with several applications of interest. This task involves dealing with changes in illumination, viewpoint variations, the articulated nature of the human body, the high flexibility of the wrist articulation, and the deformability of the hand itself. In this work, we propose an accurate and efficient automatic hand detection scheme to be applied in Human-Computer Interaction (HCI) applications in which the user is seated at the desk and, thus, only the upper body is visible. Our main hypothesis is that hand landmarks remain at a nearly constant geodesic distance from an automatically located anatomical reference point.
In a given frame, the human body is segmented first in the depth image. Then, a
graph representation of the body is built in which the geodesic paths are computed from the reference point. The dense optical flow vectors on the corresponding RGB image are used to reduce ambiguities of the geodesic paths’ connectivity, allowing to eliminate false edges interconnecting different body parts. Finally, we are able to detect the position of both hands based on invariant geodesic distances and optical flow within the body region, without involving costly learning procedures.
Address Vic; October 2013
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CCIA
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ KCE2013 Serial (down) 2323
Permanent link to this record
 
 
Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny
Title Notation-invariant patch-based wall detector in architectural floor plans Type Book Chapter
Year 2013 Publication Graphics Recognition. New Trends and Challenges Abbreviated Journal
Volume 7423 Issue Pages 79--88
Keywords
Abstract Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-36823-3 Medium
Area Expedition Conference
Notes DAG; 600.045; 600.056; 605.203 Approved no
Call Number Admin @ si @ HMS2013 Serial (down) 2322
Permanent link to this record
 
 
Author Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez
Title Combining structural and statistical strategies for unsupervised wall detection in floor plans Type Conference Article
Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper presents an evolution of the first unsupervised wall segmentation method in floor plans, that was presented by the authors in [1]. This first approach, contrarily to the existing ones, is able to segment walls independently to their notation and without the need of any pre-annotated data
to learn their visual appearance. Despite the good performance of the first approach, some specific cases, such as curved shaped walls, were not correctly segmented since they do not agree the strict structural assumptions that guide the whole methodology in order to be able to learn, in an unsupervised way, the structure of a wall. In this paper, we refine this strategy by dividing the
process in two steps. In a first step, potential wall segments are extracted unsupervisedly using a modification of [1], by restricting even more the areas considered as walls in a first moment. In a second step, these segments are used to learn and spot lost instances based on a modified version of [2], also presented by the authors. The presented combined method have been tested on
4 datasets with different notations and compared with the stateof-the-art applyed on the same datasets. The results show its adaptability to different wall notations and shapes, significantly outperforming the original approach.
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; 600.045 Approved no
Call Number Admin @ si @ HVS2013a Serial (down) 2321
Permanent link to this record
 
 
Author Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez;Josep Llados
Title Perceptual retrieval of architectural floor plans Type Conference Article
Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper proposes a runlength histogram signature as a percetual 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. Preliminary results show the interest of the proposed approach and opens a challenging research line in graphics recognition.
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; 600.045; 600.056; 600.061 Approved no
Call Number Admin @ si @ HFF2013a Serial (down) 2320
Permanent link to this record
 
 
Author Lluis Pere de las Heras; David Fernandez; Ernest Valveny; Josep Llados; Gemma Sanchez
Title Unsupervised wall detector in architectural floor plan Type Conference Article
Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 1245-1249
Keywords
Abstract Wall detection in floor plans is a crucial step in a complete floor plan recognition system. Walls define the main structure of buildings and convey essential information for the detection of other structural elements. Nevertheless, wall segmentation is a difficult task, mainly because of the lack of a standard graphical notation. The existing approaches are restricted to small group of similar notations or require the existence of pre-annotated corpus of input images to learn each new notation. In this paper we present an automatic wall segmentation system, with the ability to handle completely different notations without the need of any annotated dataset. It only takes advantage of the general knowledge that walls are a repetitive element, naturally distributed within the plan and commonly modeled by straight parallel lines. The method has been tested on four datasets of real floor plans with different notations, and compared with the state-of-the-art. The results show its suitability for different graphical notations, achieving higher recall rates than the rest of the methods while keeping a high average precision.
Address Washington; 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 1520-5363 ISBN Medium
Area Expedition Conference ICDAR
Notes DAG; 600.061; 600.056; 600.045 Approved no
Call Number Admin @ si @ HFV2013 Serial (down) 2319
Permanent link to this record
 
 
Author Dimosthenis Karatzas; Faisal Shafait; Seiichi Uchida; Masakazu Iwamura; Lluis Gomez; Sergi Robles; Joan Mas; David Fernandez; Jon Almazan; Lluis Pere de las Heras
Title ICDAR 2013 Robust Reading Competition Type Conference Article
Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 1484-1493
Keywords
Abstract This report presents the final results of the ICDAR 2013 Robust Reading Competition. The competition is structured in three Challenges addressing text extraction in different application domains, namely born-digital images, real scene images and real-scene videos. The Challenges are organised around specific tasks covering text localisation, text segmentation and word recognition. The competition took place in the first quarter of 2013, and received a total of 42 submissions over the different tasks offered. This report describes the datasets and ground truth specification, details the performance evaluation protocols used and presents the final results along with a brief summary of the participating methods.
Address Washington; 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 1520-5363 ISBN Medium
Area Expedition Conference ICDAR
Notes DAG; 600.056 Approved no
Call Number Admin @ si @ KSU2013 Serial (down) 2318
Permanent link to this record
 
 
Author Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu
Title New Opportunities for Computer Vision-Based Assistive Technology Systems for the Visually Impaired Type Journal Article
Year 2014 Publication Computer Abbreviated Journal COMP
Volume 47 Issue 4 Pages 52-58
Keywords
Abstract Computing advances and increased smartphone use gives technology system designers greater flexibility in exploiting computer vision to support visually impaired users. Understanding these users' needs will certainly provide insight for the development of improved usability of computing devices.
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 0018-9162 ISBN Medium
Area Expedition Conference
Notes LAMP; Approved no
Call Number Admin @ si @ TSR2014a Serial (down) 2317
Permanent link to this record
 
 
Author Bogdan Raducanu; Fadi Dornaika
Title Embedding new observations via sparse-coding for non-linear manifold learning Type Journal Article
Year 2014 Publication Pattern Recognition Abbreviated Journal PR
Volume 47 Issue 1 Pages 480-492
Keywords
Abstract Non-linear dimensionality reduction techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data-the out-of-sample problem. For the first aspect, the proposed solutions, in general, were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only achieved for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that the sparse representation theory not only serves for automatic graph construction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the K-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on six public face datasets. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes.
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 LAMP; Approved no
Call Number Admin @ si @ RaD2013b Serial (down) 2316
Permanent link to this record
 
 
Author Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu
Title Efficient Graph Construction for Label Propagation based Multi-observation Face Recognition Type Conference Article
Year 2013 Publication Human Behavior Understanding 4th International Workshop Abbreviated Journal
Volume 8212 Issue Pages 124-135
Keywords
Abstract Workshop on Human Behavior Understanding
Human-machine interaction is a hot topic nowadays in the communities of multimedia and computer vision. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. Recently, graph-based label propagation for multi-observation face recognition was proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot adapt optimally to the data. In this paper, we propose a novel approach for efficient and adaptive graph construction that can be used for multi-observation face recognition as well as for other recognition problems. Experimental results performed on Honda video face database, show a distinct advantage of the proposed method over the standard graph construction methods.
Address Barcelona
Corporate Author Thesis
Publisher Springer International Publishing Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-319-02713-5 Medium
Area Expedition Conference HBU
Notes OR;MV Approved no
Call Number Admin @ si @ DBR2013 Serial (down) 2315
Permanent link to this record