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Author Abel Gonzalez-Garcia; Joost Van de Weijer; Yoshua Bengio edit   pdf
openurl 
  Title (up) Image-to-image translation for cross-domain disentanglement Type Conference Article
  Year 2018 Publication 32nd Annual Conference on Neural Information Processing Systems Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Montreal; Canada; December 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 NIPS  
  Notes LAMP; 600.120 Approved no  
  Call Number Admin @ si @ GWB2018 Serial 3155  
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Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
doi  openurl
  Title (up) Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames Type Conference Article
  Year 2013 Publication 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Abbreviated Journal  
  Volume Issue Pages 7350 - 7354  
  Keywords  
  Abstract In this paper we present our image preprocessing methods as a key part of our automatic polyp localization scheme. These methods are used to assess the impact of different endoluminal scene elements when characterizing polyps. More precisely we tackle the influence of specular highlights, blood vessels and black mask surrounding the scene. Experimental results prove that the appropriate handling of these elements leads to a great improvement in polyp localization results.  
  Address Osaka; Japan; 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 1557-170X ISBN Medium  
  Area 800 Expedition Conference EMBC  
  Notes MV; 600.047; 600.060;SIAI Approved no  
  Call Number Admin @ si @ BSV2013 Serial 2286  
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Author Joan M. Nuñez; Jorge Bernal; Miquel Ferrer; Fernando Vilariño edit   pdf
doi  openurl
  Title (up) Impact of Keypoint Detection on Graph-based Characterization of Blood Vessels in Colonoscopy Videos Type Conference Article
  Year 2014 Publication CARE workshop Abbreviated Journal  
  Volume Issue Pages  
  Keywords Colonoscopy; Graph Matching; Biometrics; Vessel; Intersection  
  Abstract We explore the potential of the use of blood vessels as anatomical landmarks for developing image registration methods in colonoscopy images. An unequivocal representation of blood vessels could be used to guide follow-up methods to track lesions over different interventions. We propose a graph-based representation to characterize network structures, such as blood vessels, based on the use of intersections and endpoints. We present a study consisting of the assessment of the minimal performance a keypoint detector should achieve so that the structure can still be recognized. Experimental results prove that, even by achieving a loss of 35% of the keypoints, the descriptive power of the associated graphs to the vessel pattern is still high enough to recognize blood vessels.  
  Address Boston; USA; September 2014  
  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 CARE  
  Notes MV; DAG; 600.060; 600.047; 600.077;SIAI Approved no  
  Call Number Admin @ si @ NBF2014 Serial 2504  
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Author Anna Esposito; Italia Cirillo; Antonietta Esposito; Leopoldina Fortunati; Gian Luca Foresti; Sergio Escalera; Nikolaos Bourbakis edit  openurl
  Title (up) Impairments in decoding facial and vocal emotional expressions in high functioning autistic adults and adolescents Type Conference Article
  Year 2020 Publication Faces and Gestures in E-health and welfare workshop Abbreviated Journal  
  Volume Issue Pages 667-674  
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  Abstract  
  Address Virtual; November 2020  
  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 FGW  
  Notes HUPBA Approved no  
  Call Number Admin @ si @ ECE2020 Serial 3516  
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Author Mohammad Rouhani; Angel Sappa edit  openurl
  Title (up) Implicit B-Spline Fitting Using the 3L Algorithm Type Conference Article
  Year 2011 Publication 18th IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages 893-896  
  Keywords  
  Abstract  
  Address Brussels, Belgium  
  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 ICIP  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RoS2011a; ADAS @ adas @ Serial 1782  
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Author Mohammad Rouhani; Angel Sappa; E. Boyer edit  doi
openurl 
  Title (up) 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.  
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  Corporate Author Thesis  
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  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; 600.076 Approved no  
  Call Number Admin @ si @ RSB2015 Serial 2541  
Permanent link to this record
 

 
Author M. Altillawi; S. Li; S.M. Prakhya; Z. Liu; Joan Serrat edit  doi
openurl 
  Title (up) Implicit Learning of Scene Geometry From Poses for Global Localization Type Journal Article
  Year 2024 Publication IEEE Robotics and Automation Letters Abbreviated Journal ROBOTAUTOMLET  
  Volume 9 Issue 2 Pages 955-962  
  Keywords Localization; Localization and mapping; Deep learning for visual perception; Visual learning  
  Abstract Global visual localization estimates the absolute pose of a camera using a single image, in a previously mapped area. Obtaining the pose from a single image enables many robotics and augmented/virtual reality applications. Inspired by latest advances in deep learning, many existing approaches directly learn and regress 6 DoF pose from an input image. However, these methods do not fully utilize the underlying scene geometry for pose regression. The challenge in monocular relocalization is the minimal availability of supervised training data, which is just the corresponding 6 DoF poses of the images. In this letter, we propose to utilize these minimal available labels (i.e., poses) to learn the underlying 3D geometry of the scene and use the geometry to estimate the 6 DoF camera pose. We present a learning method that uses these pose labels and rigid alignment to learn two 3D geometric representations ( X, Y, Z coordinates ) of the scene, one in camera coordinate frame and the other in global coordinate frame. Given a single image, it estimates these two 3D scene representations, which are then aligned to estimate a pose that matches the pose label. This formulation allows for the active inclusion of additional learning constraints to minimize 3D alignment errors between the two 3D scene representations, and 2D re-projection errors between the 3D global scene representation and 2D image pixels, resulting in improved localization accuracy. During inference, our model estimates the 3D scene geometry in camera and global frames and aligns them rigidly to obtain pose in real-time. We evaluate our work on three common visual localization datasets, conduct ablation studies, and show that our method exceeds state-of-the-art regression methods' pose accuracy on all datasets.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2377-3766 ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ Serial 3857  
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Author Mohammad Rouhani; Angel Sappa edit   pdf
doi  openurl
  Title (up) 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.
 
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  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 1937  
Permanent link to this record
 

 
Author Javier Varona; Jordi Gonzalez; Ignasi Rius; Juan J. Villanueva edit  openurl
  Title (up) Importance of Detection for Video Surveillance Applications Type Journal
  Year 2008 Publication Optical Engineering, vol. 47(8), 087201/1–9 Abbreviated Journal  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number ISE @ ise @ VGR2008 Serial 998  
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Author X. Jing; David Zhang; Zhong Jin edit  openurl
  Title (up) Improved algorithm and generalized theory Type Journal
  Year 2003 Publication Pattern Recognition, 36(11): 2593–2602 (IF: 1.611) Abbreviated Journal  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ JZJ2003b Serial 429  
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Author Fei Yang; Yongmei Cheng; Joost Van de Weijer; Mikhail Mozerov edit  url
doi  openurl
  Title (up) Improved Discrete Optical Flow Estimation With Triple Image Matching Cost Type Journal Article
  Year 2020 Publication IEEE Access Abbreviated Journal ACCESS  
  Volume 8 Issue Pages 17093 - 17102  
  Keywords  
  Abstract Approaches that use more than two consecutive video frames in the optical flow estimation have a long research history. However, almost all such methods utilize extra information for a pre-processing flow prediction or for a post-processing flow correction and filtering. In contrast, this paper differs from previously developed techniques. We propose a new algorithm for the likelihood function calculation (alternatively the matching cost volume) that is used in the maximum a posteriori estimation. We exploit the fact that in general, optical flow is locally constant in the sense of time and the likelihood function depends on both the previous and the future frame. Implementation of our idea increases the robustness of optical flow estimation. As a result, our method outperforms 9% over the DCFlow technique, which we use as prototype for our CNN based computation architecture, on the most challenging MPI-Sintel dataset for the non-occluded mask metric. Furthermore, our approach considerably increases the accuracy of the flow estimation for the matching cost processing, consequently outperforming the original DCFlow algorithm results up to 50% in occluded regions and up to 9% in non-occluded regions on the MPI-Sintel dataset. The experimental section shows that the proposed method achieves state-of-the-arts results especially on the MPI-Sintel dataset.  
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  Language Summary Language Original Title  
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  Area Expedition Conference  
  Notes LAMP; 600.120 Approved no  
  Call Number Admin @ si @ YCW2020 Serial 3345  
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Author Hugo Berti; Angel Sappa; Osvaldo Agamennoni edit  openurl
  Title (up) Improved Dynamic Window Approach by Using Lyapunov Stability Criteria Type Journal
  Year 2008 Publication Latin American Applied Research Abbreviated Journal  
  Volume 38 Issue 4 Pages 289–298  
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  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ BSA2008 Serial 1056  
Permanent link to this record
 

 
Author Mikhail Mozerov; Joost Van de Weijer edit   pdf
doi  openurl
  Title (up) Improved Recursive Geodesic Distance Computation for Edge Preserving Filter Type Journal Article
  Year 2017 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP  
  Volume 26 Issue 8 Pages 3696 - 3706  
  Keywords Geodesic distance filter; color image filtering; image enhancement  
  Abstract All known recursive filters based on the geodesic distance affinity are realized by two 1D recursions applied in two orthogonal directions of the image plane. The 2D extension of the filter is not valid and has theoretically drawbacks, which lead to known artifacts. In this paper, a maximum influence propagation method is proposed to approximate the 2D extension for the
geodesic distance-based recursive filter. The method allows to partially overcome the drawbacks of the 1D recursion approach. We show that our improved recursion better approximates the true geodesic distance filter, and the application of this improved filter for image denoising outperforms the existing recursive implementation of the geodesic distance. As an application,
we consider a geodesic distance-based filter for image denoising.
Experimental evaluation of our denoising method demonstrates comparable and for several test images better results, than stateof-the-art approaches, while our algorithm is considerably fasterwith computational complexity O(8P).
 
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  Notes LAMP; ISE; 600.120; 600.098; 600.119 Approved no  
  Call Number Admin @ si @ Moz2017 Serial 2921  
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Author Marc Oliu; Ciprian Corneanu; Kamal Nasrollahi; Olegs Nikisins; Sergio Escalera; Yunlian Sun; Haiqing Li; Zhenan Sun; Thomas B. Moeslund; Modris Greitans edit  url
openurl 
  Title (up) Improved RGB-D-T based Face Recognition Type Journal Article
  Year 2016 Publication IET Biometrics Abbreviated Journal BIO  
  Volume 5 Issue 4 Pages 297 - 303  
  Keywords  
  Abstract Reliable facial recognition systems are of crucial importance in various applications from entertainment to security. Thanks to the deep-learning concepts introduced in the field, a significant improvement in the performance of the unimodal facial recognition systems has been observed in the recent years. At the same time a multimodal facial recognition is a promising approach. This study combines the latest successes in both directions by applying deep learning convolutional neural networks (CNN) to the multimodal RGB, depth, and thermal (RGB-D-T) based facial recognition problem outperforming previously published results. Furthermore, a late fusion of the CNN-based recognition block with various hand-crafted features (local binary patterns, histograms of oriented gradients, Haar-like rectangular features, histograms of Gabor ordinal measures) is introduced, demonstrating even better recognition performance on a benchmark RGB-D-T database. The obtained results in this study show that the classical engineered features and CNN-based features can complement each other for recognition purposes.  
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  Area Expedition Conference  
  Notes HuPBA;MILAB; Approved no  
  Call Number Admin @ si @ OCN2016 Serial 2854  
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Author Carlo Gatta; Oriol Pujol; Oriol Rodriguez-Leor; J. Mauri; Petia Radeva edit  openurl
  Title (up) Improved Rigid Registration of Vessel Structures using the Fast Radial Symmetry Transform Type Conference Article
  Year 2008 Publication Computer Vision for Intravascular Imaging CVII’08 Workshop Medical Image Computing and Computer–Assisted Intervention , 11th International Conference Abbreviated Journal  
  Volume Issue Pages 128–136  
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  Abstract  
  Address NY (USA)  
  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 MICCAI  
  Notes MILAB;HUPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ GPR2008b Serial 1038  
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