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Author Mohammad Rouhani; Angel Sappa; E. Boyer
Title Implicit B-Spline Surface Reconstruction Type Journal Article
Year 2015 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 24 Issue 1 Pages 22 - 32
Keywords
Abstract This paper presents a fast and flexible curve, and surface reconstruction technique based on implicit B-spline. This representation does not require any parameterization and it is locally supported. This fact has been exploited in this paper to propose a reconstruction technique through solving a sparse system of equations. This method is further accelerated to reduce the dimension to the active control lattice. Moreover, the surface smoothness and user interaction are allowed for controlling the surface. Finally, a novel weighting technique has been introduced in order to blend small patches and smooth them in the overlapping regions. The whole framework is very fast and efficient and can handle large cloud of points with very low computational cost. The experimental results show the flexibility and accuracy of the proposed algorithm to describe objects with complex topologies. Comparisons with other fitting methods highlight the superiority of the proposed approach in the presence of noise and missing data.
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 (down) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ADAS; 600.076 Approved no
Call Number Admin @ si @ RSB2015 Serial 2541
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Author M. Olivera; Angel Sappa; Victor Santos
Title A probabilistic approach for color correction in image mosaicking applications Type Journal Article
Year 2015 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 14 Issue 2 Pages 508 - 523
Keywords Color correction; image mosaicking; color transfer; color palette mapping functions
Abstract Image mosaicking applications require both geometrical and photometrical registrations between the images that compose the mosaic. This paper proposes a probabilistic color correction algorithm for correcting the photometrical disparities. First, the image to be color corrected is segmented into several regions using mean shift. Then, connected regions are extracted using a region fusion algorithm. Local joint image histograms of each region are modeled as collections of truncated Gaussians using a maximum likelihood estimation procedure. Then, local color palette mapping functions are computed using these sets of Gaussians. The color correction is performed by applying those functions to all the regions of the image. An extensive comparison with ten other state of the art color correction algorithms is presented, using two different image pair data sets. Results show that the proposed approach obtains the best average scores in both data sets and evaluation metrics and is also the most robust to failures.
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 (down) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ADAS; 600.076 Approved no
Call Number Admin @ si @ OSS2015b Serial 2554
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Author Mikhail Mozerov; Joost Van de Weijer
Title Accurate stereo matching by two step global optimization Type Journal Article
Year 2015 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 24 Issue 3 Pages 1153-1163
Keywords
Abstract In stereo matching cost filtering methods and energy minimization algorithms are considered as two different techniques. Due to their global extend energy minimization methods obtain good stereo matching results. However, they tend to fail in occluded regions, in which cost filtering approaches obtain better results. In this paper we intend to combine both approaches with the aim to improve overall stereo matching results. We show that a global optimization with a fully connected model can be solved by cost fil tering methods. Based on this observation we propose to perform stereo matching as a two-step energy minimization algorithm. We consider two MRF models: a fully connected model defined on the complete set of pixels in an image and a conventional locally connected model. We solve the energy minimization problem for the fully connected model, after which the marginal function of the solution is used as the unary potential in the locally connected MRF model. Experiments on the Middlebury stereo datasets show that the proposed method achieves state-of-the-arts results.
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 (down) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ISE; LAMP; 600.079; 600.078 Approved no
Call Number Admin @ si @ MoW2015a Serial 2568
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Author Mohammad Rouhani; Angel Sappa
Title The Richer Representation the Better Registration Type Journal Article
Year 2013 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 22 Issue 12 Pages 5036-5049
Keywords
Abstract In this paper, the registration problem is formulated as a point to model distance minimization. Unlike most of the existing works, which are based on minimizing a point-wise correspondence term, this formulation avoids the correspondence search that is time-consuming. In the first stage, the target set is described through an implicit function by employing a linear least squares fitting. This function can be either an implicit polynomial or an implicit B-spline from a coarse to fine representation. In the second stage, we show how the obtained implicit representation is used as an interface to convert point-to-point registration into point-to-implicit problem. Furthermore, we show that this registration distance is smooth and can be minimized through the Levengberg-Marquardt algorithm. All the formulations presented for both stages are compact and easy to implement. In addition, we show that our registration method can be handled using any implicit representation though some are coarse and others provide finer representations; hence, a tradeoff between speed and accuracy can be set by employing the right implicit function. Experimental results and comparisons in 2D and 3D show the robustness and the speed of convergence 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 (down) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ RoS2013 Serial 2665
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Author Fahad Shahbaz Khan; Jiaolong Xu; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez
Title Recognizing Actions through Action-specific Person Detection Type Journal Article
Year 2015 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 24 Issue 11 Pages 4422-4432
Keywords
Abstract Action recognition in still images is a challenging problem in computer vision. To facilitate comparative evaluation independently of person detection, the standard evaluation protocol for action recognition uses an oracle person detector to obtain perfect bounding box information at both training and test time. The assumption is that, in practice, a general person detector will provide candidate bounding boxes for action recognition. In this paper, we argue that this paradigm is suboptimal and that action class labels should already be considered during the detection stage. Motivated by the observation that body pose is strongly conditioned on action class, we show that: 1) the existing state-of-the-art generic person detectors are not adequate for proposing candidate bounding boxes for action classification; 2) due to limited training examples, the direct training of action-specific person detectors is also inadequate; and 3) using only a small number of labeled action examples, the transfer learning is able to adapt an existing detector to propose higher quality bounding boxes for subsequent action classification. To the best of our knowledge, we are the first to investigate transfer learning for the task of action-specific person detection in still images. We perform extensive experiments on two benchmark data sets: 1) Stanford-40 and 2) PASCAL VOC 2012. For the action detection task (i.e., both person localization and classification of the action performed), our approach outperforms methods based on general person detection by 5.7% mean average precision (MAP) on Stanford-40 and 2.1% MAP on PASCAL VOC 2012. Our approach also significantly outperforms the state of the art with a MAP of 45.4% on Stanford-40 and 31.4% on PASCAL VOC 2012. We also evaluate our action detection approach for the task of action classification (i.e., recognizing actions without localizing them). For this task, our approach, without using any ground-truth person localization at test tim- , outperforms on both data sets state-of-the-art methods, which do use person locations.
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 (down) 1057-7149 ISBN Medium
Area Expedition Conference
Notes ADAS; LAMP; 600.076; 600.079 Approved no
Call Number Admin @ si @ KXR2015 Serial 2668
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Author Lluis Garrido; M.Guerrieri; Laura Igual
Title Image Segmentation with Cage Active Contours Type Journal Article
Year 2015 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 24 Issue 12 Pages 5557 - 5566
Keywords Level sets; Mean value coordinates; Parametrized active contours; level sets; mean value coordinates
Abstract In this paper, we present a framework for image segmentation based on parametrized active contours. The evolving contour is parametrized according to a reduced set of control points that form a closed polygon and have a clear visual interpretation. The parametrization, called mean value coordinates, stems from the techniques used in computer graphics to animate virtual models. Our framework allows to easily formulate region-based energies to segment an image. In particular, we present three different local region-based energy terms: 1) the mean model; 2) the Gaussian model; 3) and the histogram model. We show the behavior of our method on synthetic and real images and compare the performance with state-of-the-art level set methods.
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 (down) 1057-7149 ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number Admin @ si @ GGI2015 Serial 2673
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Author Mikhail Mozerov; Joost Van de Weijer
Title Global Color Sparseness and a Local Statistics Prior for Fast Bilateral Filtering Type Journal Article
Year 2015 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 24 Issue 12 Pages 5842-5853
Keywords
Abstract The property of smoothing while preserving edges makes the bilateral filter a very popular image processing tool. However, its non-linear nature results in a computationally costly operation. Various works propose fast approximations to the bilateral filter. However, the majority does not generalize to vector input as is the case with color images. We propose a fast approximation to the bilateral filter for color images. The filter is based on two ideas. First, the number of colors, which occur in a single natural image, is limited. We exploit this color sparseness to rewrite the initial non-linear bilateral filter as a number of linear filter operations. Second, we impose a statistical prior to the image values that are locally present within the filter window. We show that this statistical prior leads to a closed-form solution of the bilateral filter. Finally, we combine both ideas into a single fast and accurate bilateral filter for color images. Experimental results show that our bilateral filter based on the local prior yields an extremely fast bilateral filter approximation, but with limited accuracy, which has potential application in real-time video filtering. Our bilateral filter, which combines color sparseness and local statistics, yields a fast and accurate bilateral filter approximation and obtains the state-of-the-art results.
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 (down) 1057-7149 ISBN Medium
Area Expedition Conference
Notes LAMP; 600.079;ISE Approved no
Call Number Admin @ si @ MoW2015b Serial 2689
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Author Mikhail Mozerov; Ariel Amato; Xavier Roca; Jordi Gonzalez
Title Solving the Multi Object Occlusion Problem in a Multiple Camera Tracking System Type Journal
Year 2009 Publication Pattern Recognition and Image Analysis Abbreviated Journal
Volume 19 Issue 1 Pages 165-171
Keywords
Abstract An efficient method to overcome adverse effects of occlusion upon object tracking is presented. The method is based on matching paths of objects in time and solves a complex occlusion-caused problem of merging separate segments of the same path.
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 (down) 1054-6618 ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number ISE @ ise @ MAR2009a Serial 1160
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Author Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Fernando Azpiroz; Petia Radeva
Title Automatic Detection of Intestinal Juices in Wireless Capsule Video Endoscopy Type Conference Article
Year 2006 Publication 18th International Conference on Pattern Recognition Abbreviated Journal
Volume 4 Issue Pages 719-722
Keywords Clinical diagnosis , Endoscopes , Fluids and secretions , Gabor filters , Hospitals , Image sequence analysis , Intestines , Lighting , Shape , Visualization
Abstract Wireless capsule video endoscopy is a novel and challenging clinical technique, whose major reported drawback relates to the high amount of time needed for video visualization. In this paper, we propose a method for the rejection of the parts of the video resulting not valid for analysis by means of automatic detection of intestinal juices. We applied Gabor filters for the characterization of the bubble-like shape of intestinal juices in fasting patients. Our method achieves a significant reduction in visualization time, with no relevant loss of valid frames. The proposed approach is easily extensible to other image analysis scenarios where the described pattern of bubbles can be found.
Address Hong Kong
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 (down) 1051-4651 ISBN 0-7695-2521-0 Medium
Area 800 Expedition Conference ICPR
Notes MV;OR;MILAB;SIAI Approved no
Call Number BCNPCL @ bcnpcl @ VSV2006b; IAM @ iam @ VSV2006g Serial 727
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Author Jaume Amores
Title Vocabulary-based Approaches for Multiple-Instance Data: a Comparative Study Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 4246–4250
Keywords
Abstract Multiple Instance Learning (MIL) has become a hot topic and many different algorithms have been proposed in the last years. Despite this fact, there is a lack of comparative studies that shed light into the characteristics of the different methods and their behavior in different scenarios. In this paper we provide such an analysis. We include methods from different families, and pay special attention to vocabulary-based approaches, a new family of methods that has not received much attention in the MIL literature. The empirical comparison includes seven databases from four heterogeneous domains, implementations of eight popular MIL methods, and a study of the behavior under synthetic conditions. Based on this analysis, we show that, with an appropriate implementation, vocabulary-based approaches outperform other MIL methods in most of the cases, showing in general a more consistent performance.
Address Istanbul, Turkey
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 (down) 1051-4651 ISBN 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes ADAS Approved no
Call Number ADAS @ adas @ Amo2010 Serial 1295
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Author Fadi Dornaika; Bogdan Raducanu
Title Person-specific face shape estimation under varying head pose from single snapshots Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 3496–3499
Keywords
Abstract This paper presents a new method for person-specific face shape estimation under varying head pose of a previously unseen person from a single image. We describe a featureless approach based on a deformable 3D model and a learned face subspace. The proposed approach is based on maximizing a likelihood measure associated with a learned face subspace, which is carried out by a stochastic and genetic optimizer. We conducted the experiments on a subset of Honda Video Database showing the feasibility and robustness of the proposed approach. For this reason, our approach could lend itself nicely to complex frameworks involving 3D face tracking and face gesture recognition in monocular videos.
Address Istanbul, Turkey
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 (down) 1051-4651 ISBN 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ DoR2010b Serial 1361
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Author Francesco Ciompi; Oriol Pujol; Petia Radeva
Title A meta-learning approach to Conditional Random Fields using Error-Correcting Output Codes Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 710–713
Keywords
Abstract We present a meta-learning framework for the design of potential functions for Conditional Random Fields. The design of both node potential and edge potential is formulated as a classification problem where margin classifiers are used. The set of state transitions for the edge potential is treated as a set of different classes, thus defining a multi-class learning problem. The Error-Correcting Output Codes (ECOC) technique is used to deal with the multi-class problem. Furthermore, the point defined by the combination of margin classifiers in the ECOC space is interpreted in a probabilistic manner, and the obtained distance values are then converted into potential values. The proposed model exhibits very promising results when applied to two real detection problems.
Address Istanbul;Turkey
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 (down) 1051-4651 ISBN 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes MILAB;HUPBA Approved no
Call Number BCNPCL @ bcnpcl @ CPR2010a Serial 1365
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Author David Augusto Rojas; Fahad Shahbaz Khan; Joost Van de Weijer
Title The Impact of Color on Bag-of-Words based Object Recognition Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 1549–1553
Keywords
Abstract In recent years several works have aimed at exploiting color information in order to improve the bag-of-words based image representation. There are two stages in which color information can be applied in the bag-of-words framework. Firstly, feature detection can be improved by choosing highly informative color-based regions. Secondly, feature description, typically focusing on shape, can be improved with a color description of the local patches. Although both approaches have been shown to improve results the combined merits have not yet been analyzed. Therefore, in this paper we investigate the combined contribution of color to both the feature detection and extraction stages. Experiments performed on two challenging data sets, namely Flower and Pascal VOC 2009; clearly demonstrate that incorporating color in both feature detection and extraction significantly improves the overall performance.
Address Istanbul (Turkey)
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 (down) 1051-4651 ISBN 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes Approved no
Call Number CAT @ cat @ RKW2010 Serial 1415
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Author Murad Al Haj; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca
Title Reactive object tracking with a single PTZ camera Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 1690–1693
Keywords
Abstract In this paper we describe a novel approach to reactive tracking of moving targets with a pan-tilt-zoom camera. The approach uses an extended Kalman filter to jointly track the object position in the real world, its velocity in 3D and the camera intrinsics, in addition to the rate of change of these parameters. The filter outputs are used as inputs to PID controllers which continuously adjust the camera motion in order to reactively track the object at a constant image velocity while simultaneously maintaining a desirable target scale in the image plane. We provide experimental results on simulated and real tracking sequences to show how our tracker is able to accurately estimate both 3D object position and camera intrinsics with very high precision over a wide range of focal lengths.
Address Istanbul (Turkey)
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 (down) 1051-4651 ISBN 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes ISE Approved no
Call Number DAG @ dag @ ABG2010 Serial 1418
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Author Anjan Dutta; Umapada Pal; Alicia Fornes; Josep Llados
Title An Efficient Staff Removal Technique from Printed Musical Documents Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 1965–1968
Keywords
Abstract Staff removal is an important preprocessing step of the Optical Music Recognition (OMR). The process aims to remove the stafflines from a musical document and retain only the musical symbols, later these symbols are used effectively to identify the music information. This paper proposes a simple but robust method to remove stafflines from printed musical scores. In the proposed methodology we have considered a staffline segment as a horizontal linkage of vertical black runs with uniform height. We have used the neighbouring properties of a staffline segment to validate it as a true segment. We have considered the dataset along with the deformations described in for evaluation purpose. From experimentation we have got encouraging results.
Address Istanbul (Turkey)
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 (down) 1051-4651 ISBN 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes DAG Approved no
Call Number DAG @ dag @ DPF2010 Serial 1420
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