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Author | Yunchao Gong; Svetlana Lazebnik; Albert Gordo; Florent Perronnin | ||||
Title | Iterative quantization: A procrustean approach to learning binary codes for Large-Scale Image Retrieval | Type | Journal Article | ||
Year | 2012 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 35 | Issue | 12 | Pages | 2916-2929 |
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Abstract | This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multi-class spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or “classemes” on the ImageNet dataset. | ||||
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ISSN | 0162-8828 | ISBN | 978-1-4577-0394-2 | Medium | |
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Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ GLG 2012b | Serial | 2008 | ||
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Author | Dimosthenis Karatzas;Ch. Lioutas | ||||
Title | Software Package Development for Electron Diffraction Image Analysis | Type | Conference Article | ||
Year | 1998 | Publication | Proceedings of the XIV Solid State Physics National Conference | Abbreviated Journal | |
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Address | Ioannina, Greece | ||||
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Notes | DAG | Approved | no | ||
Call Number | IAM @ iam @ KaL1998 | Serial | 2045 | ||
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Author | Angel Sappa; David Geronimo; Fadi Dornaika; Mohammad Rouhani; Antonio Lopez | ||||
Title | Moving object detection from mobile platforms using stereo data registration | Type | Book Chapter | ||
Year | 2012 | Publication | Computational Intelligence paradigms in advanced pattern classification | Abbreviated Journal | |
Volume | 386 | Issue | Pages | 25-37 | |
Keywords | pedestrian detection | ||||
Abstract | This chapter describes a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three main stages. Initially, feature points are extracted and tracked through consecutive 2D frames. Then, a RANSAC based approach is used for registering two point sets, with known correspondences in the 3D space. The computed 3D rigid displacement is used to map two consecutive 3D point clouds into the same coordinate system by means of the quaternion method. Finally, moving objects correspond to those areas with large 3D registration errors. Experimental results show the viability of the proposed approach to detect moving objects like vehicles or pedestrians in different urban scenarios. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Marek R. Ogiela; Lakhmi C. Jain | |
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ISSN | 1860-949X | ISBN | 978-3-642-24048-5 | Medium | |
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ SGD2012 | Serial | 2061 | ||
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Author | Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez | ||||
Title | Trajectory-Based Abnormality Categorization for Learning Route Patterns in Surveillance | Type | Book Chapter | ||
Year | 2012 | Publication | Detection and Identification of Rare Audiovisual Cues, Studies in Computational Intelligence | Abbreviated Journal | |
Volume | 384 | Issue | 3 | Pages | 87-95 |
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Abstract | The recognition of abnormal behaviors in video sequences has raised as a hot topic in video understanding research. Particularly, an important challenge resides on automatically detecting abnormality. However, there is no convention about the types of anomalies that training data should derive. In surveillance, these are typically detected when new observations differ substantially from observed, previously learned behavior models, which represent normality. This paper focuses on properly defining anomalies within trajectory analysis: we propose a hierarchical representation conformed by Soft, Intermediate, and Hard Anomaly, which are identified from the extent and nature of deviation from learned models. Towards this end, a novel Gaussian Mixture Model representation of learned route patterns creates a probabilistic map of the image plane, which is applied to detect and classify anomalies in real-time. Our method overcomes limitations of similar existing approaches, and performs correctly even when the tracking is affected by different sources of noise. The reliability of our approach is demonstrated experimentally. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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ISSN | 1860-949X | ISBN | 978-3-642-24033-1 | Medium | |
Area | Expedition | Conference | |||
Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ BFR2012 | Serial | 2062 | ||
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Author | Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus | ||||
Title | Color Naming | Type | Book Chapter | ||
Year | 2012 | Publication | Color in Computer Vision: Fundamentals and Applications | Abbreviated Journal | |
Volume | Issue | 17 | Pages | 287-317 | |
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Publisher | John Wiley & Sons, Ltd. | Place of Publication | Editor | Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek | |
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Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ WBV2012 | Serial | 2063 | ||
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Author | Xavier Perez Sala; Laura Igual; Sergio Escalera; Cecilio Angulo | ||||
Title | Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models | Type | Book Chapter | ||
Year | 2012 | Publication | Vision Robotics: Technologies for Machine Learning and Vision Applications | Abbreviated Journal | |
Volume | Issue | 2 | Pages | 23-42 | |
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Abstract | Different methodologies of uniform sampling over the rotation group, SO(3), for building unbiased 2D shape models from 3D objects are introduced and reviewed in this chapter. State-of-the-art non uniform sampling approaches are discussed, and uniform sampling methods using Euler angles and quaternions are introduced. Moreover, since presented work is oriented to model building applications, it is not limited to general discrete methods to obtain uniform 3D rotations, but also from a continuous point of view in the case of Procrustes Analysis. | ||||
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Publisher | IGI-Global | Place of Publication | Editor | ||
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Notes | MILAB;HuPBA | Approved | no | ||
Call Number | Admin @ si @ PIE2012 | Serial | 2064 | ||
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Author | Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Oscar Vilarroya; Petia Radeva | ||||
Title | A Supervised Graph-cut Deformable Model for Brain MRI Segmentation. Deformation models: tracking, animation and applications | Type | Book Chapter | ||
Year | 2012 | Publication | Computational Vision and Biomechanics | Abbreviated Journal | |
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Publisher | Springer Netherlands | Place of Publication | Editor | ||
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Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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ISSN | ISBN | 978-94-007-5445-4 | Medium | ||
Area | Expedition | Conference | |||
Notes | MILAB;HuPBA | Approved | no | ||
Call Number | Admin @ si @ ISH2012b | Serial | 2066 | ||
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Author | Angel Sappa; George A. Triantafyllid | ||||
Title | Computer Graphics and Imaging | Type | Book Whole | ||
Year | 2012 | Publication | Computer Graphics and Imaging | Abbreviated Journal | |
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Address | Crete, Greece | ||||
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ISSN | ISBN | 978-0-88986-921-9 | Medium | ||
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Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ Sap2012 | Serial | 2067 | ||
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Author | Theo Gevers; Arjan Gijsenij; Joost Van de Weijer; J.M. Geusebroek | ||||
Title | Color in Computer Vision: Fundamentals and Applications | Type | Book Whole | ||
Year | 2012 | Publication | Color in Computer Vision: Fundamentals and Applications | Abbreviated Journal | |
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Publisher | The Wiley-IS&T Series in Imaging Science and Technology | Place of Publication | Editor | ||
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ISSN | ISBN | 978-0-470-89084-4 | Medium | ||
Area | Expedition | Conference | |||
Notes | ALTRES;ISE | Approved | no | ||
Call Number | Admin @ si @ GGG2012a | Serial | 2068 | ||
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Author | Mario Hernandez; Joao Sanchez; Jordi Vitria | ||||
Title | Selected papers from Iberian Conference on Pattern Recognition and Image Analysis | Type | Book Whole | ||
Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | |
Volume | 45 | Issue | 9 | Pages | 3047-3582 |
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ISSN | 0031-3203 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ HSV2012 | Serial | 2069 | ||
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Author | Ernest Valveny; Robert Benavente; Agata Lapedriza; Miquel Ferrer; Jaume Garcia; Gemma Sanchez | ||||
Title | Adaptation of a computer programming course to the EXHE requirements: evaluation five years later | Type | Miscellaneous | ||
Year | 2012 | Publication | European Journal of Engineering Education | Abbreviated Journal | |
Volume | 37 | Issue | 3 | Pages | 243-254 |
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Notes | DAG; CIC; OR; invisible;MV | Approved | no | ||
Call Number | Admin @ si @ VBL2012 | Serial | 2070 | ||
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Author | Michal Drozdzal; Petia Radeva; Santiago Segui; Laura Igual; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria | ||||
Title | System and method for automatic detection of in vivo contraction video sequences | Type | Patent | ||
Year | 2012 | Publication | US20120057766 | Abbreviated Journal | |
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Abstract | Publication date: 2012/3/8 | ||||
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Notes | MILAB; OR;MV | Approved | no | ||
Call Number | Admin @ si @ DRS2012b | Serial | 2071 | ||
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Author | Shida Beigpour | ||||
Title | Illumination and object reflectance modeling | Type | Book Whole | ||
Year | 2013 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | More realistic and accurate models of the scene illumination and object reflectance can greatly improve the quality of many computer vision and computer graphics tasks. Using such model, a more profound knowledge about the interaction of light with object surfaces can be established which proves crucial to a variety of computer vision applications. In the current work, we investigate the various existing approaches to illumination and reflectance modeling and form an analysis on their shortcomings in capturing the complexity of real-world scenes. Based on this analysis we propose improvements to different aspects of reflectance and illumination estimation in order to more realistically model the real-world scenes in the presence of complex lighting phenomena (i.e, multiple illuminants, interreflections and shadows). Moreover, we captured our own multi-illuminant dataset which consists of complex scenes and illumination conditions both outdoor and in laboratory conditions. In addition we investigate the use of synthetic data to facilitate the construction of datasets and improve the process of obtaining ground-truth information. | ||||
Address | Barcelona | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Joost Van de Weijer;Ernest Valveny | |
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Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ Bei2013 | Serial | 2267 | ||
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Author | Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga | ||||
Title | Coloresia: An Interactive Colour Perception Device for the Visually Impaired | Type | Book Chapter | ||
Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications | Abbreviated Journal | |
Volume | 48 | Issue | Pages | 47-66 | |
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Abstract | A significative percentage of the human population suffer from impairments in their capacity to distinguish or even see colours. For them, everyday tasks like navigating through a train or metro network map becomes demanding. We present a novel technique for extracting colour information from everyday natural stimuli and presenting it to visually impaired users as pleasant, non-invasive sound. This technique was implemented inside a Personal Digital Assistant (PDA) portable device. In this implementation, colour information is extracted from the input image and categorised according to how human observers segment the colour space. This information is subsequently converted into sound and sent to the user via speakers or headphones. In the original implementation, it is possible for the user to send its feedback to reconfigure the system, however several features such as these were not implemented because the current technology is limited.We are confident that the full implementation will be possible in the near future as PDA technology improves. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
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Notes | CIC; 600.052; 605.203 | Approved | no | ||
Call Number | Admin @ si @ GBP2013 | Serial | 2266 | ||
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Author | Santiago Segui; Laura Igual; Jordi Vitria | ||||
Title | Bagged One Class Classifiers in the Presence of Outliers | Type | Journal Article | ||
Year | 2013 | Publication | International Journal of Pattern Recognition and Artificial Intelligence | Abbreviated Journal | IJPRAI |
Volume | 27 | Issue | 5 | Pages | 1350014-1350035 |
Keywords | One-class Classifier; Ensemble Methods; Bagging and Outliers | ||||
Abstract | The problem of training classifiers only with target data arises in many applications where non-target data are too costly, difficult to obtain, or not available at all. Several one-class classification methods have been presented to solve this problem, but most of the methods are highly sensitive to the presence of outliers in the target class. Ensemble methods have therefore been proposed as a powerful way to improve the classification performance of binary/multi-class learning algorithms by introducing diversity into classifiers.
However, their application to one-class classification has been rather limited. In this paper, we present a new ensemble method based on a non-parametric weighted bagging strategy for one-class classification, to improve accuracy in the presence of outliers. While the standard bagging strategy assumes a uniform data distribution, the method we propose here estimates a probability density based on a forest structure of the data. This assumption allows the estimation of data distribution from the computation of simple univariate and bivariate kernel densities. Experiments using original and noisy versions of 20 different datasets show that bagging ensemble methods applied to different one-class classifiers outperform base one-class classification methods. Moreover, we show that, in noisy versions of the datasets, the non-parametric weighted bagging strategy we propose outperforms the classical bagging strategy in a statistically significant way. |
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Notes | OR; 600.046;MV | Approved | no | ||
Call Number | Admin @ si @ SIV2013 | Serial | 2256 | ||
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