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Author Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell
Title Portmanteau Vocabularies for Multi-Cue Image Representation Type Conference Article
Year 2011 Publication 25th Annual Conference on Neural Information Processing Systems Abbreviated Journal
Volume Issue Pages
Keywords (up)
Abstract We describe a novel technique for feature combination in the bag-of-words model of image classification. Our approach builds discriminative compound words from primitive cues learned independently from training images. Our main observation is that modeling joint-cue distributions independently is more statistically robust for typical classification problems than attempting to empirically estimate the dependent, joint-cue distribution directly. We use Information theoretic vocabulary compression to find discriminative combinations of cues and the resulting vocabulary of portmanteau words is compact, has the cue binding property, and supports individual weighting of cues in the final image representation. State-of-the-art results on both the Oxford Flower-102 and Caltech-UCSD Bird-200 datasets demonstrate the effectiveness of our technique compared to other, significantly more complex approaches to multi-cue image representation
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 NIPS
Notes CIC Approved no
Call Number Admin @ si @ KWB2011 Serial 1865
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Author Jordi Roca; C. Alejandro Parraga; Maria Vanrell
Title Categorical Focal Colours are Structurally Invariant Under Illuminant Changes Type Conference Article
Year 2011 Publication European Conference on Visual Perception Abbreviated Journal
Volume Issue Pages 196
Keywords (up)
Abstract The visual system perceives the colour of surfaces approximately constant under changes of illumination. In this work, we investigate how stable is the perception of categorical \“focal\” colours and their interrelations with varying illuminants and simple chromatic backgrounds. It has been proposed that best examples of colour categories across languages cluster in small regions of the colour space and are restricted to a set of 11 basic terms (Kay and Regier, 2003 Proceedings of the National Academy of Sciences of the USA 100 9085\–9089). Following this, we developed a psychophysical paradigm that exploits the ability of subjects to reliably reproduce the most representative examples of each category, adjusting multiple test patches embedded in a coloured Mondrian. The experiment was run on a CRT monitor (inside a dark room) under various simulated illuminants. We modelled the recorded data for each subject and adapted state as a 3D interconnected structure (graph) in Lab space. The graph nodes were the subject\’s focal colours at each adaptation state. The model allowed us to get a better distance measure between focal structures under different illuminants. We found that perceptual focal structures tend to be preserved better than the structures of the physical \“ideal\” colours under illuminant changes.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Perception 40 Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ECVP
Notes CIC Approved no
Call Number Admin @ si @ RPV2011 Serial 1867
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Author Sergio Escalera; Ana Puig; Oscar Amoros; Maria Salamo
Title Intelligent GPGPU Classification in Volume Visualization: a framework based on Error-Correcting Output Codes Type Journal Article
Year 2011 Publication Computer Graphics Forum Abbreviated Journal CGF
Volume 30 Issue 7 Pages 2107-2115
Keywords (up)
Abstract IF JCR 1.455 2010 25/99
In volume visualization, the definition of the regions of interest is inherently an iterative trial-and-error process finding out the best parameters to classify and render the final image. Generally, the user requires a lot of expertise to analyze and edit these parameters through multi-dimensional transfer functions. In this paper, we present a framework of intelligent methods to label on-demand multiple regions of interest. These methods can be split into a two-level GPU-based labelling algorithm that computes in time of rendering a set of labelled structures using the Machine Learning Error-Correcting Output Codes (ECOC) framework. In a pre-processing step, ECOC trains a set of Adaboost binary classifiers from a reduced pre-labelled data set. Then, at the testing stage, each classifier is independently applied on the features of a set of unlabelled samples and combined to perform multi-class labelling. We also propose an alternative representation of these classifiers that allows to highly parallelize the testing stage. To exploit that parallelism we implemented the testing stage in GPU-OpenCL. The empirical results on different data sets for several volume structures shows high computational performance and classification accuracy.
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 MILAB; HuPBA Approved no
Call Number Admin @ si @ EPA2011 Serial 1881
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Author Mario Rojas; David Masip; A. Todorov; Jordi Vitria
Title Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models Type Journal Article
Year 2011 Publication PloS one Abbreviated Journal Plos
Volume 6 Issue 8 Pages e23323
Keywords (up)
Abstract JCR Impact Factor 2010: 4.411
Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions
Address
Corporate Author Thesis
Publisher Public Library of Science 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 OR;MV Approved no
Call Number Admin @ si @ RMT2011 Serial 1883
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Author Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva
Title On the Design of Low Redundancy Error-Correcting Output Codes Type Book Chapter
Year 2011 Publication Ensembles in Machine Learning Applications Abbreviated Journal
Volume 373 Issue 2 Pages 21-38
Keywords (up)
Abstract The classification of large number of object categories is a challenging trend in the Pattern Recognition field. In the literature, this is often addressed using an ensemble of classifiers . In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for combining classifiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a compact design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best compact ECOC code configuration. The results over several public UCI data sets and different multi-class Computer Vision problems show that the proposed methodology obtains comparable (even better) results than the state-of-the-art ECOC methodologies with far less number of dichotomizers.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1860-949X ISBN 978-3-642-22909-1 Medium
Area Expedition Conference
Notes MILAB; OR;HuPBA;MV Approved no
Call Number Admin @ si @ BEB2011b Serial 1886
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Author Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera
Title Introducing the Separability Matrix for Error Correcting Output Codes Coding Type Conference Article
Year 2011 Publication 10th International Conference on Multiple Classifier Systems Abbreviated Journal
Volume 6713 Issue Pages 227-236
Keywords (up)
Abstract Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results.
Address Napoles, Italy
Corporate Author Thesis
Publisher Springer-Verlag Berlin, Heidelberg Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-21556-8 Medium
Area Expedition Conference MCS
Notes MILAB; OR;HuPBA;MV Approved no
Call Number Admin @ si @ BPB2011b Serial 1887
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Author Antonio Hernandez; Carlos Primo; Sergio Escalera
Title Automatic user interaction correction via Multi-label Graph cuts Type Conference Article
Year 2011 Publication In ICCV 2011 1st IEEE International Workshop on Human Interaction in Computer Vision HICV Abbreviated Journal
Volume Issue Pages 1276-1281
Keywords (up)
Abstract Most applications in image segmentation requires from user interaction in order to achieve accurate results. However, user wants to achieve the desired segmentation accuracy reducing effort of manual labelling. In this work, we extend standard multi-label α-expansion Graph Cut algorithm so that it analyzes the interaction of the user in order to modify the object model and improve final segmentation of objects. The approach is inspired in the fact that fast user interactions may introduce some pixel errors confusing object and background. Our results with different degrees of user interaction and input errors show high performance of the proposed approach on a multi-label human limb segmentation problem compared with classical α-expansion algorithm.
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 978-1-4673-0062-9 Medium
Area Expedition Conference HICV
Notes MILAB; HuPBA Approved no
Call Number Admin @ si @ HPE2011 Serial 1892
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Author Miguel Reyes; Gabriel Dominguez; Sergio Escalera
Title Feature Weighting in Dynamic Time Warping for Gesture Recognition in Depth Data Type Conference Article
Year 2011 Publication 1st IEEE Workshop on Consumer Depth Cameras for Computer Vision Abbreviated Journal
Volume Issue Pages 1182-1188
Keywords (up)
Abstract We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability. Feature Weighting in Dynamic Time Warping is then applied for recognizing begin-end of gestures in data sequences. The obtained results recognizing several gestures in depth data show high performance compared with classical Dynamic Time Warping 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 ISBN 978-1-4673-0062-9 Medium
Area Expedition Conference CDC4CV
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ RDE2011 Serial 1893
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Author Michal Drozdzal; Santiago Segui; Petia Radeva; Jordi Vitria; Laura Igual
Title System and Method for Displaying Motility Events in an in Vivo Image Stream Type Patent
Year 2011 Publication US 61/592,786 Abbreviated Journal
Volume Issue Pages
Keywords (up)
Abstract
Address Given Imaging
Corporate Author US Patent Office 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 MILAB; OR;MV Approved no
Call Number Admin @ si @ DSR2011 Serial 1897
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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 (up)
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 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 (up)
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 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 (up)
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 1934
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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 (up)
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 1978
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Author Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru
Title Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs Type Conference Article
Year 2011 Publication Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal
Volume 7029 Issue Pages 223-230
Keywords (up)
Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations.
Address Nice, France
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor In H. Yoshida et al
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ABDI
Notes IAM; MV Approved no
Call Number VGB2011 Serial 2036
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Author Jaime Moreno; Xavier Otazu
Title Image compression algorithm based on Hilbert scanning of embedded quadTrees: an introduction of the Hi-SET coder Type Conference Article
Year 2011 Publication IEEE International Conference on Multimedia and Expo Abbreviated Journal
Volume Issue Pages 1-6
Keywords (up)
Abstract In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. The implementation of the proposed coder is developed for gray-scale and color image compression. Hi-SET compressed images are, on average, 6.20dB better than the ones obtained by other compression techniques based on the Hilbert scanning. Moreover, Hi-SET improves the image quality in 1.39dB and 1.00dB in gray-scale and color compression, respectively, when compared with JPEG2000 coder.
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 1945-7871 ISBN 978-1-61284-348-3 Medium
Area Expedition Conference ICME
Notes CIC Approved no
Call Number Admin @ si @ MoO2011a Serial 2176
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