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Author Alejandro Gonzalez Alzate
Title Evaluation of spatiotemporal descriptors for pedestrian detection in video sequences Type Report
Year 2011 Publication CVC Technical Report Abbreviated Journal
Volume 166 Issue Pages
Keywords
Abstract
Address Bellaterra (Spain)
Corporate Author Computer Vision Center Thesis Master's 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 ADAS Approved no
Call Number Admin @ si @ Gon2011 Serial (up) 1932
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Author Yainuvis Socarras
Title Image segmentation for improving pedestrian detection Type Report
Year 2011 Publication CVC Technical Report Abbreviated Journal
Volume 167 Issue Pages
Keywords
Abstract
Address Bellaterra (Spain)
Corporate Author Computer Vision Center Thesis Master's 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 ADAS; Approved no
Call Number Admin @ si @ Soc2011 Serial (up) 1933
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Author Maria del Camp Davesa
Title Human action categorization in image sequences Type Report
Year 2011 Publication CVC Technical Report Abbreviated Journal
Volume 169 Issue Pages
Keywords
Abstract
Address Bellaterra (Spain)
Corporate Author Computer Vision Center Thesis Master's 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 CiC;CIC Approved no
Call Number Admin @ si @ Dav2011 Serial (up) 1934
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Author Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell; Antonio Lopez
Title Color Attributes for Object Detection Type Conference Article
Year 2012 Publication 25th IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 3306-3313
Keywords pedestrian detection
Abstract State-of-the-art object detectors typically use shape information as a low level feature representation to capture the local structure of an object. This paper shows that early fusion of shape and color, as is popular in image classification,
leads to a significant drop in performance for object detection. Moreover, such approaches also yields suboptimal results for object categories with varying importance of color and shape.
In this paper we propose the use of color attributes as an explicit color representation for object detection. Color attributes are compact, computationally efficient, and when combined with traditional shape features provide state-ofthe-
art results for object detection. Our method is tested on the PASCAL VOC 2007 and 2009 datasets and results clearly show that our method improves over state-of-the-art techniques despite its simplicity. We also introduce a new dataset consisting of cartoon character images in which color plays a pivotal role. On this dataset, our approach yields a significant gain of 14% in mean AP over conventional state-of-the-art methods.
Address Providence; Rhode Island; USA;
Corporate Author Thesis
Publisher IEEE Xplore Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1063-6919 ISBN 978-1-4673-1226-4 Medium
Area Expedition Conference CVPR
Notes ADAS; CIC; Approved no
Call Number Admin @ si @ KRW2012 Serial (up) 1935
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Author Monica Piñol
Title Adaptative Vocabulary Tree for Image Classification using Reinforcement Learning Type Report
Year 2010 Publication CVC Technical Report Abbreviated Journal
Volume 162 Issue Pages
Keywords
Abstract
Address Bellaterra (Barcelona)
Corporate Author Computer Vision Center Thesis Master's 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 ADAS Approved no
Call Number Admin @ si @ Piñ2010 Serial (up) 1936
Permanent link to this record
 
 
Author Mohammad Rouhani; Angel Sappa
Title Implicit Polynomial Representation through a Fast Fitting Error Estimation Type Journal Article
Year 2012 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 21 Issue 4 Pages 2089-2098
Keywords
Abstract Impact Factor
This paper presents a simple distance estimation for implicit polynomial fitting. It is computed as the height of a simplex built between the point and the surface (i.e., a triangle in 2-D or a tetrahedron in 3-D), which is used as a coarse but reliable estimation of the orthogonal distance. The proposed distance can be described as a function of the coefficients of the implicit polynomial. Moreover, it is differentiable and has a smooth behavior . Hence, it can be used in any gradient-based optimization. In this paper, its use in a Levenberg-Marquardt framework is shown, which is particularly devoted for nonlinear least squares problems. The proposed estimation is a generalization of the gradient-based distance estimation, which is widely used in the literature. Experimental results, both in 2-D and 3-D data sets, are provided. Comparisons with state-of-the-art techniques are presented, showing the advantages of the proposed approach.
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 1057-7149 ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ RoS2012b; ADAS @ adas @ Serial (up) 1937
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Author Jean-Marc Ogier; Wenyin Liu; Josep Llados (eds)
Title Graphics Recognition: Achievements, Challenges, and Evolution Type Book Whole
Year 2010 Publication 8th International Workshop GREC 2009. Abbreviated Journal
Volume 6020 Issue Pages
Keywords
Abstract
Address La Rochelle
Corporate Author Thesis
Publisher Springer Link Place of Publication Editor Jean-Marc Ogier; Wenyin Liu; Josep Llados
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-13727-3 Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number Admin @ si @ OLL2010 Serial (up) 1976
Permanent link to this record
 
 
Author Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner
Title Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation Type Conference Article
Year 2011 Publication In Proceedings of the Sixth International Workshop on Digital Technologies in Cartographic Heritage Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
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 CartoHerit
Notes DAG Approved no
Call Number Admin @ si @ RRL2011b Serial (up) 1978
Permanent link to this record
 
 
Author Javier Marin; David Geronimo; David Vazquez; Antonio Lopez
Title Pedestrian Detection: Exploring Virtual Worlds Type Book Chapter
Year 2012 Publication Handbook of Pattern Recognition: Methods and Application Abbreviated Journal
Volume 5 Issue Pages 145-162
Keywords Virtual worlds; Pedestrian Detection; Domain Adaptation
Abstract Handbook of pattern recognition will include contributions from university educators and active research experts. This Handbook is intended to serve as a basic reference on methods and applications of pattern recognition. The primary aim of this handbook is providing the community of pattern recognition with a readable, easy to understand resource that covers introductory, intermediate and advanced topics with equal clarity. Therefore, the Handbook of pattern recognition can serve equally well as reference resource and as classroom textbook. Contributions cover all methods, techniques and applications of pattern recognition. A tentative list of relevant topics might include: 1- Statistical, structural, syntactic pattern recognition. 2- Neural networks, machine learning, data mining. 3- Discrete geometry, algebraic, graph-based techniques for pattern recognition. 4- Face recognition, Signal analysis, image coding and processing, shape and texture analysis. 5- Document processing, text and graphics recognition, digital libraries. 6- Speech recognition, music analysis, multimedia systems. 7- Natural language analysis, information retrieval. 8- Biometrics, biomedical pattern analysis and information systems. 9- Other scientific, engineering, social and economical applications of pattern recognition. 10- Special hardware architectures, software packages for pattern recognition.
Address
Corporate Author Thesis
Publisher iConcept Press Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-477554-82-1 Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ MGV2012 Serial (up) 1979
Permanent link to this record
 
 
Author Yainuvis Socarras; David Vazquez; Antonio Lopez; David Geronimo; Theo Gevers
Title Improving HOG with Image Segmentation: Application to Human Detection Type Conference Article
Year 2012 Publication 11th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal
Volume 7517 Issue Pages 178-189
Keywords Segmentation; Pedestrian Detection
Abstract In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descriptor information and (ii) take advantage of the information of image segmentation, which in fact is likely to be used in other stages of the detection system such as candidate generation or refinement.
We test our technique in the INRIA person dataset, which was originally developed to test HOG, embedding it in a human detection system. The well-known segmentation method, mean-shift (from smaller to larger super-pixels), and different methods to re-weight the original descriptor (constant, region-luminance, color or texture-dependent) has been evaluated. We achieve performance improvements of 4:47% in detection rate through the use of differences of color between contour pixel neighborhoods as re-weighting function.
Address Brno, Czech Republic
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor J. Blanc-Talon et al.
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-33139-8 Medium
Area Expedition Conference ACIVS
Notes ADAS;ISE Approved no
Call Number ADAS @ adas @ SLV2012 Serial (up) 1980
Permanent link to this record
 
 
Author David Vazquez; Antonio Lopez; Daniel Ponsa
Title Unsupervised Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection Type Conference Article
Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 3492 - 3495
Keywords Pedestrian Detection; Domain Adaptation; Virtual worlds
Abstract Vision-based object detectors are crucial for different applications. They rely on learnt object models. Ideally, we would like to deploy our vision system in the scenario where it must operate, and lead it to self-learn how to distinguish the objects of interest, i.e., without human intervention. However, the learning of each object model requires labelled samples collected through a tiresome manual process. For instance, we are interested in exploring the self-training of a pedestrian detector for driver assistance systems. Our first approach to avoid manual labelling consisted in the use of samples coming from realistic computer graphics, so that their labels are automatically available [12]. This would make possible the desired self-training of our pedestrian detector. However, as we showed in [14], between virtual and real worlds it may be a dataset shift. In order to overcome it, we propose the use of unsupervised domain adaptation techniques that avoid human intervention during the adaptation process. In particular, this paper explores the use of the transductive SVM (T-SVM) learning algorithm in order to adapt virtual and real worlds for pedestrian detection (Fig. 1).
Address Tsukuba Science City, Japan
Corporate Author Thesis
Publisher IEEE Place of Publication Tsukuba Science City, JAPAN Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1051-4651 ISBN 978-1-4673-2216-4 Medium
Area Expedition Conference ICPR
Notes ADAS Approved no
Call Number ADAS @ adas @ VLP2012 Serial (up) 1981
Permanent link to this record
 
 
Author Jon Almazan; Alicia Fornes; Ernest Valveny
Title A non-rigid appearance model for shape description and recognition Type Journal Article
Year 2012 Publication Pattern Recognition Abbreviated Journal PR
Volume 45 Issue 9 Pages 3105--3113
Keywords Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition
Abstract In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM approach.
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 0031-3203 ISBN Medium
Area Expedition Conference
Notes DAG Approved no
Call Number DAG @ dag @ AFV2012 Serial (up) 1982
Permanent link to this record
 
 
Author Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny
Title A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection Type Conference Article
Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 453-458
Keywords
Abstract In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase.
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 978-1-4673-2262-1 Medium
Area Expedition Conference ICFHR
Notes DAG Approved no
Call Number DAG @ dag @ AFF2012 Serial (up) 1983
Permanent link to this record
 
 
Author Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny
Title Efficient Exemplar Word Spotting Type Conference Article
Year 2012 Publication 23rd British Machine Vision Conference Abbreviated Journal
Volume Issue Pages 67.1- 67.11
Keywords
Abstract In this paper we propose an unsupervised segmentation-free method for word spotting in document images.
Documents are represented with a grid of HOG descriptors, and a sliding window approach is used to locate the document regions that are most similar to the query. We use the exemplar SVM framework to produce a better representation of the query in an unsupervised way. Finally, the document descriptors are precomputed and compressed with Product Quantization. This offers two advantages: first, a large number of documents can be kept in RAM memory at the same time. Second, the sliding window becomes significantly faster since distances between quantized HOG descriptors can be precomputed. Our results significantly outperform other segmentation-free methods in the literature, both in accuracy and in speed and memory usage.
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 1-901725-46-4 Medium
Area Expedition Conference BMVC
Notes DAG Approved no
Call Number DAG @ dag @ AGF2012 Serial (up) 1984
Permanent link to this record
 
 
Author Ferran Poveda; Enric Marti; Debora Gil; Francesc Carreras; Manel Ballester
Title Helical Structure of Ventricular Anatomy by Diffusion Tensor Cardiac MR Tractography Type Journal Article
Year 2012 Publication Journal of American College of Cardiology Abbreviated Journal JACC
Volume 5 Issue 7 Pages 754-755
Keywords
Abstract It is widely accepted that myocardial fiber architecture plays a critical role in myocardial contractility and relaxation (1). However, there is a lack of consensus about the distribution of the myocardial fibers and their spatial arrangement in the left and right ventricles. An understanding of the cardiac architecture should benefit the ventricular functional assessment, left ventricular reconstructive surgery planning, or resynchronization therapy in heart failure. Researchers have proposed several conceptual models to describe the architecture of the heart, ranging from gross dissection to histological presentation. The cardiac mesh model (2) proposes that the myocytes are arranged longitudinally and radially change their angulation along the myocardial depth. By contrast, the helical ventricular myocardial model states that the ventricular myocardium is a continuous anatomical helical layout of myocardial fibers (1
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 1936-878X ISBN Medium
Area Expedition Conference
Notes IAM Approved no
Call Number IAM @ iam @ PMG2012 Serial (up) 1985
Permanent link to this record