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| Author | Bhaskar Chakraborty; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca | ||||
| Title | Human Action Recognition Using an Ensemble of Body-Part Detectors | Type | Journal Article | ||
| Year | 2013 | Publication | Expert Systems | Abbreviated Journal | EXSY |
| Volume | 30 | Issue | 2 | Pages | 101-114 |
Keywords  |
Human action recognition;body-part detection;hidden Markov model | ||||
| Abstract | This paper describes an approach to human action recognition based on a probabilistic optimization model of body parts using hidden Markov model (HMM). Our method is able to distinguish between similar actions by only considering the body parts having major contribution to the actions, for example, legs for walking, jogging and running; arms for boxing, waving and clapping. We apply HMMs to model the stochastic movement of the body parts for action recognition. The HMM construction uses an ensemble of body-part detectors, followed by grouping of part detections, to perform human identification. Three example-based body-part detectors are trained to detect three components of the human body: the head, legs and arms. These detectors cope with viewpoint changes and self-occlusions through the use of ten sub-classifiers that detect body parts over a specific range of viewpoints. Each sub-classifier is a support vector machine trained on features selected for the discriminative power for each particular part/viewpoint combination. Grouping of these detections is performed using a simple geometric constraint model that yields a viewpoint-invariant human detector. We test our approach on three publicly available action datasets: the KTH dataset, Weizmann dataset and HumanEva dataset. Our results illustrate that with a simple and compact representation we can achieve robust recognition of human actions comparable to the most complex, state-of-the-art methods. | ||||
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| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ CBG2013 | Serial | 1809 | ||
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| Author | Ferran Poveda; Debora Gil; Enric Marti; Albert Andaluz; Manel Ballester;Francesc Carreras Costa | ||||
| Title | Helical structure of the cardiac ventricular anatomy assessed by Diffusion Tensor Magnetic Resonance Imaging multi-resolution tractography | Type | Journal Article | ||
| Year | 2013 | Publication | Revista Española de Cardiología | Abbreviated Journal | REC |
| Volume | 66 | Issue | 10 | Pages | 782-790 |
| Keywords |
Heart;Diffusion magnetic resonance imaging;Diffusion tractography;Helical heart;Myocardial ventricular band. | ||||
| Abstract | Deep understanding of myocardial structure linking morphology and function of the heart would unravel crucial knowledge for medical and surgical clinical procedures and studies. Several conceptual models of myocardial fiber organization have been proposed but the lack of an automatic and objective methodology prevented an agreement. We sought to deepen in this knowledge through advanced computer graphic representations of the myocardial fiber architecture by diffusion tensor magnetic resonance imaging (DT-MRI).
We performed automatic tractography reconstruction of unsegmented DT-MRI canine heart datasets coming from the public database of the Johns Hopkins University. Full scale tractographies have been build with 200 seeds and are composed by streamlines computed on the vectorial field of primary eigenvectors given at the diffusion tensor volumes. Also, we introduced a novel multi-scale visualization technique in order to obtain a simplified tractography. This methodology allowed to keep the main geometric features of the fiber tracts, making easier to decipher the main properties of the architectural organization of the heart. On the analysis of the output from our tractographic representations we found exact correlation with low-level details of myocardial architecture, but also with the more abstract conceptualization of a continuous helical ventricular myocardial fiber array. Objective analysis of myocardial architecture by an automated method, including the entire myocardium and using several 3D levels of complexity, reveals a continuous helical myocardial fiber arrangement of both right and left ventricles, supporting the anatomical model of the helical ventricular myocardial band described by Torrent-Guasp. |
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| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Area | Expedition | Conference | |||
| Notes | IAM; 600.044; 600.060 | Approved | no | ||
| Call Number | IAM @ iam @ PGM2013 | Serial | 2194 | ||
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| Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera | ||||
| Title | A Genetic-based Subspace Analysis Method for Improving Error-Correcting Output Coding | Type | Journal Article | ||
| Year | 2013 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 46 | Issue | 10 | Pages | 2830-2839 |
| Keywords |
Error Correcting Output Codes; Evolutionary computation; Multiclass classification; Feature subspace; Ensemble classification | ||||
| Abstract | Two key factors affecting the performance of Error Correcting Output Codes (ECOC) in multiclass classification problems are the independence of binary classifiers and the problem-dependent coding design. In this paper, we propose an evolutionary algorithm-based approach to the design of an application-dependent codematrix in the ECOC framework. The central idea of this work is to design a three-dimensional codematrix, where the third dimension is the feature space of the problem domain. In order to do that, we consider the feature space in the design process of the codematrix with the aim of improving the independence and accuracy of binary classifiers. The proposed method takes advantage of some basic concepts of ensemble classification, such as diversity of classifiers, and also benefits from the evolutionary approach for optimizing the three-dimensional codematrix, taking into account the problem domain. We provide a set of experimental results using a set of benchmark datasets from the UCI Machine Learning Repository, as well as two real multiclass Computer Vision problems. Both sets of experiments are conducted using two different base learners: Neural Networks and Decision Trees. The results show that the proposed method increases the classification accuracy in comparison with the state-of-the-art ECOC coding techniques. | ||||
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| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0031-3203 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ BGE2013a | Serial | 2247 | ||
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| Author | David Roche; Debora Gil; Jesus Giraldo | ||||
| Title | Detecting loss of diversity for an efficient termination of EAs | Type | Conference Article | ||
| Year | 2013 | Publication | 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing | Abbreviated Journal | |
| Volume | Issue | Pages | 561 - 566 | ||
| Keywords |
EA termination; EA population diversity; EA steady state | ||||
| Abstract | Termination of Evolutionary Algorithms (EA) at its steady state so that useless iterations are not performed is a main point for its efficient application to black-box problems. Many EA algorithms evolve while there is still diversity in their population and, thus, they could be terminated by analyzing the behavior some measures of EA population diversity. This paper presents a numeric approximation to steady states that can be used to detect the moment EA population has lost its diversity for EA termination. Our condition has been applied to 3 EA paradigms based on diversity and a selection of functions
covering the properties most relevant for EA convergence. Experiments show that our condition works regardless of the search space dimension and function landscape. |
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| Address | Timisoara; Rumania; | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-4799-3035-7 | Medium | ||
| Area | Expedition | Conference | SYNASC | ||
| Notes | IAM; 600.044; 600.060; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ RGG2013c | Serial | 2299 | ||
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| Author | S.Grau; Anna Puig; Sergio Escalera; Maria Salamo; Oscar Amoros | ||||
| Title | Efficient complementary viewpoint selection in volume rendering | Type | Conference Article | ||
| Year | 2013 | Publication | 21st WSCG Conference on Computer Graphics, | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords |
Dual camera; Visualization; Interactive Interfaces; Dynamic Time Warping. | ||||
| Abstract | A major goal of visualization is to appropriately express knowledge of scientific data. Generally, gathering visual information contained in the volume data often requires a lot of expertise from the final user to setup the parameters of the visualization. One way of alleviating this problem is to provide the position of inner structures with different viewpoint locations to enhance the perception and construction of the mental image. To this end, traditional illustrations use two or three different views of the regions of interest. Similarly, with the aim of assisting the users to easily place a good viewpoint location, this paper proposes an automatic and interactive method that locates different complementary viewpoints from a reference camera in volume datasets. Specifically, the proposed method combines the quantity of information each camera provides for each structure and the shape similarity of the projections of the remaining viewpoints based on Dynamic Time Warping. The selected complementary viewpoints allow a better understanding of the focused structure in several applications. Thus, the user interactively receives feedback based on several viewpoints that helps him to understand the visual information. A live-user evaluation on different data sets show a good convergence to useful complementary viewpoints. | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-808694374-9 | Medium | ||
| Area | Expedition | Conference | WSCG | ||
| Notes | HuPBA; 600.046;MILAB | Approved | no | ||
| Call Number | Admin @ si @ GPE2013a | Serial | 2255 | ||
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| Author | Jiaolong Xu; Sebastian Ramos; Xu Hu; David Vazquez; Antonio Lopez | ||||
| Title | Multi-task Bilinear Classifiers for Visual Domain Adaptation | Type | Conference Article | ||
| Year | 2013 | Publication | Advances in Neural Information Processing Systems Workshop | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords |
Domain Adaptation; Pedestrian Detection; ADAS | ||||
| Abstract | We propose a method that aims to lessen the significant accuracy degradation
that a discriminative classifier can suffer when it is trained in a specific domain (source domain) and applied in a different one (target domain). The principal reason for this degradation is the discrepancies in the distribution of the features that feed the classifier in different domains. Therefore, we propose a domain adaptation method that maps the features from the different domains into a common subspace and learns a discriminative domain-invariant classifier within it. Our algorithm combines bilinear classifiers and multi-task learning for domain adaptation. The bilinear classifier encodes the feature transformation and classification parameters by a matrix decomposition. In this way, specific feature transformations for multiple domains and a shared classifier are jointly learned in a multi-task learning framework. Focusing on domain adaptation for visual object detection, we apply this method to the state-of-the-art deformable part-based model for cross domain pedestrian detection. Experimental results show that our method significantly avoids the domain drift and improves the accuracy when compared to several baselines. |
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| Address | Lake Tahoe; Nevada; USA; December 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | NIPSW | ||
| Notes | ADAS; 600.054; 600.057; 601.217;ISE | Approved | no | ||
| Call Number | ADAS @ adas @ XRH2013 | Serial | 2340 | ||
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| Author | Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez | ||||
| Title | DA-DPM Pedestrian Detection | Type | Conference Article | ||
| Year | 2013 | Publication | ICCV Workshop on Reconstruction meets Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords |
Domain Adaptation; Pedestrian Detection | ||||
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| Area | Expedition | Conference | ICCVW-RR | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ XRV2013 | Serial | 2569 | ||
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| Author | Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers | ||||
| Title | Adapting Pedestrian Detection from Synthetic to Far Infrared Images | Type | Conference Article | ||
| Year | 2013 | Publication | ICCV Workshop on Visual Domain Adaptation and Dataset Bias | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords |
Domain Adaptation; Far Infrared; Pedestrian Detection | ||||
| Abstract | We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes. | ||||
| Address | Sydney; Australia; December 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Sydney, Australy | Editor | ||
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICCVW-VisDA | ||
| Notes | ADAS; 600.054; 600.055; 600.057; 601.217;ISE | Approved | no | ||
| Call Number | ADAS @ adas @ SRV2013 | Serial | 2334 | ||
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| Author | Jaume Gibert; Ernest Valveny; Horst Bunke | ||||
| Title | Embedding of Graphs with Discrete Attributes Via Label Frequencies | Type | Journal Article | ||
| Year | 2013 | Publication | International Journal of Pattern Recognition and Artificial Intelligence | Abbreviated Journal | IJPRAI |
| Volume | 27 | Issue | 3 | Pages | 1360002-1360029 |
| Keywords |
Discrete attributed graphs; graph embedding; graph classification | ||||
| Abstract | Graph-based representations of patterns are very flexible and powerful, but they are not easily processed due to the lack of learning algorithms in the domain of graphs. Embedding a graph into a vector space solves this problem since graphs are turned into feature vectors and thus all the statistical learning machinery becomes available for graph input patterns. In this work we present a new way of embedding discrete attributed graphs into vector spaces using node and edge label frequencies. The methodology is experimentally tested on graph classification problems, using patterns of different nature, and it is shown to be competitive to state-of-the-art classification algorithms for graphs, while being computationally much more efficient. | ||||
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| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ GVB2013 | Serial | 2305 | ||
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| Author | Jorge Bernal; David Vazquez (eds) | ||||
| Title | Computer vision Trends and Challenges | Type | Book Whole | ||
| Year | 2013 | Publication | Computer vision Trends and Challenges | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords |
CVCRD; Computer Vision | ||||
| Abstract | This book contains the papers presented at the Eighth CVC Workshop on Computer Vision Trends and Challenges (CVCR&D'2013). The workshop was held at the Computer Vision Center (Universitat Autònoma de Barcelona), the October 25th, 2013. The CVC workshops provide an excellent opportunity for young researchers and project engineers to share new ideas and knowledge about the progress of their work, and also, to discuss about challenges and future perspectives. In addition, the workshop is the welcome event for new people that recently have joined the institute.
The program of CVCR&D is organized in a single-track single-day workshop. It comprises several sessions dedicated to specific topics. For each session, a doctor working on the topic introduces the general research lines. The PhD students expose their specific research. A poster session will be held for open questions. Session topics cover the current research lines and development projects of the CVC: Medical Imaging, Medical Imaging, Color & Texture Analysis, Object Recognition, Image Sequence Evaluation, Advanced Driver Assistance Systems, Machine Vision, Document Analysis, Pattern Recognition and Applications. We want to thank all paper authors and Program Committee members. Their contribution shows that the CVC has a dynamic, active, and promising scientific community. We hope you all enjoy this Eighth workshop and we are looking forward to meeting you and new people next year in the Ninth CVCR&D. |
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| Publisher | Place of Publication | Editor | Jorge Bernal; David Vazquez | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-940902-2-6 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | ADAS @ adas @ BeV2013 | Serial | 2339 | ||
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| Author | V.C.Kieu; Alicia Fornes; M. Visani; N.Journet ; Anjan Dutta | ||||
| Title | The ICDAR/GREC 2013 Music Scores Competition on Staff Removal | Type | Conference Article | ||
| Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords |
Competition; Music scores; Staff Removal | ||||
| Abstract | The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we propose a staff removal competition where we simulate old music scores. Thus, we have created a new set of images, which contain noise and 3D distortions. This paper describes the distortion methods, metrics, the participant’s methods and the obtained results. | ||||
| Address | Bethlehem; PA; USA; August 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| Area | Expedition | Conference | GREC | ||
| Notes | DAG; 600.045; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ KFV2013 | Serial | 2337 | ||
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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Sadiq Ali; Michael Felsberg | ||||
| Title | Evaluating the impact of color on texture recognition | Type | Conference Article | ||
| Year | 2013 | Publication | 15th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
| Volume | 8047 | Issue | Pages | 154-162 | |
| Keywords |
Color; Texture; image representation | ||||
| Abstract | State-of-the-art texture descriptors typically operate on grey scale images while ignoring color information. A common way to obtain a joint color-texture representation is to combine the two visual cues at the pixel level. However, such an approach provides sub-optimal results for texture categorisation task.
In this paper we investigate how to optimally exploit color information for texture recognition. We evaluate a variety of color descriptors, popular in image classification, for texture categorisation. In addition we analyze different fusion approaches to combine color and texture cues. Experiments are conducted on the challenging scenes and 10 class texture datasets. Our experiments clearly suggest that in all cases color names provide the best performance. Late fusion is the best strategy to combine color and texture. By selecting the best color descriptor with optimal fusion strategy provides a gain of 5% to 8% compared to texture alone on scenes and texture datasets. |
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| Address | York; UK; August 2013 | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-40260-9 | Medium | |
| Area | Expedition | Conference | CAIP | ||
| Notes | CIC; 600.048 | Approved | no | ||
| Call Number | Admin @ si @ KWA2013 | Serial | 2263 | ||
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| Author | Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
| Title | Blood Vessel Characterization in Colonoscopy Images to Improve Polyp Localization | Type | Conference Article | ||
| Year | 2013 | Publication | Proceedings of the International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | 1 | Issue | Pages | 162-171 | |
| Keywords |
Colonoscopy; Blood vessel; Linear features; Valley detection | ||||
| Abstract | This paper presents an approach to mitigate the contribution of blood vessels to the energy image used at different tasks of automatic colonoscopy image analysis. This goal is achieved by introducing a characterization of endoluminal scene objects which allows us to differentiate between the trace of 2-dimensional visual objects,such as vessels, and shades from 3-dimensional visual objects, such as folds. The proposed characterization is based on the influence that the object shape has in the resulting visual feature, and it leads to the development of a blood vessel attenuation algorithm. A database consisting of manually labelled masks was built in order to test the performance of our method, which shows an encouraging success in blood vessel mitigation while keeping other structures intact. Moreover, by extending our method to the only available polyp localization
algorithm tested on a public database, blood vessel mitigation proved to have a positive influence on the overall performance. |
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| Address | Barcelona; February 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | SciTePress | Place of Publication | Editor | ||
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| Area | 800 | Expedition | Conference | VISIGRAPP | |
| Notes | MV; 600.054; 600.057;SIAI | Approved | no | ||
| Call Number | IAM @ iam @ NBS2013 | Serial | 2198 | ||
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| Author | Javier Marin; David Vazquez; Antonio Lopez; Jaume Amores; Bastian Leibe | ||||
| Title | Random Forests of Local Experts for Pedestrian Detection | Type | Conference Article | ||
| Year | 2013 | Publication | 15th IEEE International Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 2592 - 2599 | ||
| Keywords |
ADAS; Random Forest; Pedestrian Detection | ||||
| Abstract | Pedestrian detection is one of the most challenging tasks in computer vision, and has received a lot of attention in the last years. Recently, some authors have shown the advantages of using combinations of part/patch-based detectors in order to cope with the large variability of poses and the existence of partial occlusions. In this paper, we propose a pedestrian detection method that efficiently combines multiple local experts by means of a Random Forest ensemble. The proposed method works with rich block-based representations such as HOG and LBP, in such a way that the same features are reused by the multiple local experts, so that no extra computational cost is needed with respect to a holistic method. Furthermore, we demonstrate how to integrate the proposed approach with a cascaded architecture in order to achieve not only high accuracy but also an acceptable efficiency. In particular, the resulting detector operates at five frames per second using a laptop machine. We tested the proposed method with well-known challenging datasets such as Caltech, ETH, Daimler, and INRIA. The method proposed in this work consistently ranks among the top performers in all the datasets, being either the best method or having a small difference with the best one. | ||||
| Address | Sydney; Australia; December 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | IEEE | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1550-5499 | ISBN | Medium | ||
| Area | Expedition | Conference | ICCV | ||
| Notes | ADAS; 600.057; 600.054 | Approved | no | ||
| Call Number | ADAS @ adas @ MVL2013 | Serial | 2333 | ||
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| Author | Enric Marti; Ferran Poveda; Antoni Gurgui; Jaume Rocarias; Debora Gil; Aura Hernandez-Sabate | ||||
| Title | Una experiencia de estructura, funcionamiento y evaluación de la asignatura de graficos por computador con metodologia de aprendizaje basado en proyectos | Type | Miscellaneous | ||
| Year | 2013 | Publication | IV Congreso Internacional UNIVEST | Abbreviated Journal | |
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| Abstract | IV Congreso Internacional UNIVEST | ||||
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| Area | Expedition | Conference | UNIVEST | ||
| Notes | IAM; ADAS | Approved | no | ||
| Call Number | Admin @ si @ MPG2013b | Serial | 2384 | ||
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