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| Author | David Vazquez | ||||
| Title | Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection | Type | Book Whole | ||
| Year | 2013 | Publication | PhD Thesis, Universitat de Barcelona-CVC | Abbreviated Journal | |
| Volume | 1 | Issue | 1 | Pages | 1-105 |
| Keywords | Pedestrian Detection; Domain Adaptation | ||||
| Abstract | Pedestrian detection is of paramount interest for many applications, e.g. Advanced Driver Assistance Systems, Intelligent Video Surveillance and Multimedia systems. Most promising pedestrian detectors rely on appearance-based classifiers trained with annotated data. However, the required annotation step represents an intensive and subjective task for humans, what makes worth to minimize their intervention in this process by using computational tools like realistic virtual worlds. The reason to use these kind of tools relies in the fact that they allow the automatic generation of precise and rich annotations of visual information. Nevertheless, the use of this kind of data comes with the following question: can a pedestrian appearance model learnt with virtual-world data work successfully for pedestrian detection in real-world scenarios?. To answer this question, we conduct different experiments that suggest a positive answer. However, the pedestrian classifiers trained with virtual-world data can suffer the so called dataset shift problem as real-world based classifiers does. Accordingly, we have designed different domain adaptation techniques to face this problem, all of them integrated in a same framework (V-AYLA). We have explored different methods to train a domain adapted pedestrian classifiers by collecting a few pedestrian samples from the target domain (real world) and combining them with many samples of the source domain (virtual world). The extensive experiments we present show that pedestrian detectors developed within the V-AYLA framework do achieve domain adaptation. Ideally, we would like to adapt our system without any human intervention. Therefore, as a first proof of concept we also propose an unsupervised domain adaptation technique that avoids human intervention during the adaptation process. To the best of our knowledge, this Thesis work is the first demonstrating adaptation of virtual and real worlds for developing an object detector. Last but not least, we also assessed a different strategy to avoid the dataset shift that consists in collecting real-world samples and retrain with them in such a way that no bounding boxes of real-world pedestrians have to be provided. We show that the generated classifier is competitive with respect to the counterpart trained with samples collected by manually annotating pedestrian bounding boxes. The results presented on this Thesis not only end with a proposal for adapting a virtual-world pedestrian detector to the real world, but also it goes further by pointing out a new methodology that would allow the system to adapt to different situations, which we hope will provide the foundations for future research in this unexplored area. | ||||
| Address | Barcelona | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Barcelona | Editor | Antonio Lopez;Daniel Ponsa |
| Language | English | Summary Language | Original Title | ||
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| ISSN | ISBN | 978-84-940530-1-6 | Medium | ||
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| Notes | adas | Approved | yes | ||
| Call Number | ADAS @ adas @ Vaz2013 | Serial | 2276 | ||
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| Author | Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados | ||||
| Title | Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces | Type | Book Chapter | ||
| Year | 2013 | Publication | Graph Embedding for Pattern Analysis | Abbreviated Journal | |
| Volume | Issue | Pages | 1-26 | ||
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| Abstract | Ability to recognize patterns is among the most crucial capabilities of human beings for their survival, which enables them to employ their sophisticated neural and cognitive systems [1], for processing complex audio, visual, smell, touch, and taste signals. Man is the most complex and the best existing system of pattern recognition. Without any explicit thinking, we continuously compare, classify, and identify huge amount of signal data everyday [2], starting from the time we get up in the morning till the last second we fall asleep. This includes recognizing the face of a friend in a crowd, a spoken word embedded in noise, the proper key to lock the door, smell of coffee, the voice of a favorite singer, the recognition of alphabetic characters, and millions of more tasks that we perform on regular basis. | ||||
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| Publisher | Springer New York | Place of Publication | Editor | ||
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| ISSN | ISBN | 978-1-4614-4456-5 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ LRL2013b | Serial | 2271 | ||
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| Author | Isabel Guitart; Jordi Conesa; Luis Villarejo; Agata Lapedriza; David Masip; Antoni Perez; Elena Planas | ||||
| Title | Opinion Mining on Educational Resources at the Open University of Catalonia | Type | Conference Article | ||
| Year | 2013 | Publication | 3rd International Workshop on Adaptive Learning via Interactive, Collaborative and Emotional approaches. In conjunction with CISIS 2013: The 7th International Conference on Complex, Intelligent, and Software Intensive Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 385 - 390 | ||
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| Abstract | In order to make improvements to teaching, it is vital to know what students think of the way they are taught. With that purpose in mind, exhaustively analyzing the forums associated with the subjects taught at the Universitat Oberta de Cataluya (UOC) would be extremely helpful, as the university's students often post comments on their learning experiences in them. Exploiting the content of such forums is not a simple undertaking. The volume of data involved is very large, and performing the task manually would require a great deal of effort from lecturers. As a first step to solve this problem, we propose a tool to automatically analyze the posts in forums of communities of UOC students and teachers, with a view to systematically mining the opinions they contain. This article defines the architecture of such tool and explains how lexical-semantic and language technology resources can be used to that end. For pilot testing purposes, the tool has been used to identify students' opinions on the UOC's Business Intelligence master's degree course during the last two years. The paper discusses the results of such test. The contribution of this paper is twofold. Firstly, it demonstrates the feasibility of using natural language parsing techniques to help teachers to make decisions. Secondly, it introduces a simple tool that can be refined and adapted to a virtual environment for the purpose in question. | ||||
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| ISSN | ISBN | 978-0-7695-4992-7 | Medium | ||
| Area | Expedition | Conference | ALICE | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | GCV2013 | Serial | 2268 | ||
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| Author | Jose Manuel Alvarez; Theo Gevers; Ferran Diego; Antonio Lopez | ||||
| Title | Road Geometry Classification by Adaptative Shape Models | Type | Journal Article | ||
| Year | 2013 | Publication | IEEE Transactions on Intelligent Transportation Systems | Abbreviated Journal | TITS |
| Volume | 14 | Issue | 1 | Pages | 459-468 |
| Keywords | road detection | ||||
| Abstract | Vision-based road detection is important for different applications in transportation, such as autonomous driving, vehicle collision warning, and pedestrian crossing detection. Common approaches to road detection are based on low-level road appearance (e.g., color or texture) and neglect of the scene geometry and context. Hence, using only low-level features makes these algorithms highly depend on structured roads, road homogeneity, and lighting conditions. Therefore, the aim of this paper is to classify road geometries for road detection through the analysis of scene composition and temporal coherence. Road geometry classification is proposed by building corresponding models from training images containing prototypical road geometries. We propose adaptive shape models where spatial pyramids are steered by the inherent spatial structure of road images. To reduce the influence of lighting variations, invariant features are used. Large-scale experiments show that the proposed road geometry classifier yields a high recognition rate of 73.57% ± 13.1, clearly outperforming other state-of-the-art methods. Including road shape information improves road detection results over existing appearance-based methods. Finally, it is shown that invariant features and temporal information provide robustness against disturbing imaging conditions. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1524-9050 | ISBN | Medium | ||
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| Notes | ADAS;ISE | Approved | no | ||
| Call Number | Admin @ si @ AGD2013;; ADAS @ adas @ | Serial | 2269 | ||
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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 | |
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| Area | Expedition | Conference | CartoHerit | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ RRL2011b | Serial | 1978 | ||
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| Author | Yainuvis Socarras; David Vazquez; Antonio Lopez; David Geronimo; Theo Gevers | ||||
| Title | Improving HOG with Image Segmentation: Application to Human Detection | Type | Conference Article | ||
| Year | 2012 | Publication | 11th International Conference on Advanced Concepts for Intelligent Vision Systems | Abbreviated Journal | |
| Volume | 7517 | Issue | Pages | 178-189 | |
| Keywords | Segmentation; Pedestrian Detection | ||||
| Abstract | In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descriptor information and (ii) take advantage of the information of image segmentation, which in fact is likely to be used in other stages of the detection system such as candidate generation or refinement.
We test our technique in the INRIA person dataset, which was originally developed to test HOG, embedding it in a human detection system. The well-known segmentation method, mean-shift (from smaller to larger super-pixels), and different methods to re-weight the original descriptor (constant, region-luminance, color or texture-dependent) has been evaluated. We achieve performance improvements of 4:47% in detection rate through the use of differences of color between contour pixel neighborhoods as re-weighting function. |
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| Address | Brno, Czech Republic | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | J. Blanc-Talon et al. | |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title |
Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-33139-8 | Medium | |
| Area | Expedition | Conference | ACIVS | ||
| Notes | ADAS;ISE | Approved | no | ||
| Call Number | ADAS @ adas @ SLV2012 | Serial | 1980 | ||
| Permanent link to this record | |||||
| Author | David Vazquez; Antonio Lopez; Daniel Ponsa | ||||
| Title | Unsupervised Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection | Type | Conference Article | ||
| Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 3492 - 3495 | ||
| Keywords | Pedestrian Detection; Domain Adaptation; Virtual worlds | ||||
| Abstract | Vision-based object detectors are crucial for different applications. They rely on learnt object models. Ideally, we would like to deploy our vision system in the scenario where it must operate, and lead it to self-learn how to distinguish the objects of interest, i.e., without human intervention. However, the learning of each object model requires labelled samples collected through a tiresome manual process. For instance, we are interested in exploring the self-training of a pedestrian detector for driver assistance systems. Our first approach to avoid manual labelling consisted in the use of samples coming from realistic computer graphics, so that their labels are automatically available [12]. This would make possible the desired self-training of our pedestrian detector. However, as we showed in [14], between virtual and real worlds it may be a dataset shift. In order to overcome it, we propose the use of unsupervised domain adaptation techniques that avoid human intervention during the adaptation process. In particular, this paper explores the use of the transductive SVM (T-SVM) learning algorithm in order to adapt virtual and real worlds for pedestrian detection (Fig. 1). | ||||
| Address | Tsukuba Science City, Japan | ||||
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| Publisher | IEEE | Place of Publication | Tsukuba Science City, JAPAN | Editor | |
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1051-4651 | ISBN | 978-1-4673-2216-4 | Medium | |
| Area | Expedition | Conference | ICPR | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ VLP2012 | Serial | 1981 | ||
| Permanent link to this record | |||||
| Author | Jon Almazan; Alicia Fornes; Ernest Valveny | ||||
| Title | A non-rigid appearance model for shape description and recognition | Type | Journal Article | ||
| Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 45 | Issue | 9 | Pages | 3105--3113 |
| Keywords | Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition | ||||
| Abstract | In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM approach. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0031-3203 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ AFV2012 | Serial | 1982 | ||
| Permanent link to this record | |||||
| Author | Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny | ||||
| Title | A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection | Type | Conference Article | ||
| Year | 2012 | Publication | 13th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 453-458 | ||
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| Abstract | In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-4673-2262-1 | Medium | ||
| Area | Expedition | Conference | ICFHR | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ AFF2012 | Serial | 1983 | ||
| Permanent link to this record | |||||
| Author | Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny | ||||
| Title | Efficient Exemplar Word Spotting | Type | Conference Article | ||
| Year | 2012 | Publication | 23rd British Machine Vision Conference | Abbreviated Journal | |
| Volume | Issue | Pages | 67.1- 67.11 | ||
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| Abstract | In this paper we propose an unsupervised segmentation-free method for word spotting in document images.
Documents are represented with a grid of HOG descriptors, and a sliding window approach is used to locate the document regions that are most similar to the query. We use the exemplar SVM framework to produce a better representation of the query in an unsupervised way. Finally, the document descriptors are precomputed and compressed with Product Quantization. This offers two advantages: first, a large number of documents can be kept in RAM memory at the same time. Second, the sliding window becomes significantly faster since distances between quantized HOG descriptors can be precomputed. Our results significantly outperform other segmentation-free methods in the literature, both in accuracy and in speed and memory usage. |
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 1-901725-46-4 | Medium | ||
| Area | Expedition | Conference | BMVC | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ AGF2012 | Serial | 1984 | ||
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| Author | Ferran Poveda; Enric Marti; Debora Gil; Francesc Carreras; Manel Ballester | ||||
| Title | Helical Structure of Ventricular Anatomy by Diffusion Tensor Cardiac MR Tractography | Type | Journal Article | ||
| Year | 2012 | Publication | Journal of American College of Cardiology | Abbreviated Journal | JACC |
| Volume | 5 | Issue | 7 | Pages | 754-755 |
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| Abstract | It is widely accepted that myocardial fiber architecture plays a critical role in myocardial contractility and relaxation (1). However, there is a lack of consensus about the distribution of the myocardial fibers and their spatial arrangement in the left and right ventricles. An understanding of the cardiac architecture should benefit the ventricular functional assessment, left ventricular reconstructive surgery planning, or resynchronization therapy in heart failure. Researchers have proposed several conceptual models to describe the architecture of the heart, ranging from gross dissection to histological presentation. The cardiac mesh model (2) proposes that the myocytes are arranged longitudinally and radially change their angulation along the myocardial depth. By contrast, the helical ventricular myocardial model states that the ventricular myocardium is a continuous anatomical helical layout of myocardial fibers (1 | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1936-878X | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ PMG2012 | Serial | 1985 | ||
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| Author | Ferran Poveda; Debora Gil;Enric Marti | ||||
| Title | Multi-resolution DT-MRI cardiac tractography | Type | Conference Article | ||
| Year | 2012 | Publication | Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges | Abbreviated Journal | |
| Volume | 7746 | Issue | Pages | 270-277 | |
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| Abstract | Even using objective measures from DT-MRI no consensus about myocardial architecture has been achieved so far. Streamlining provides good reconstructions at low level of detail, but falls short to give global abstract interpretations. In this paper, we present a multi-resolution methodology that is able to produce simplified representations of cardiac architecture. Our approach produces a reduced set of tracts that are representative of the main geometric features of myocardial anatomical structure. Experiments show that fiber geometry is preserved along reductions, which validates the simplified model for interpretation of cardiac architecture. | ||||
| Address | Nice, France | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title |
Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-36960-5 | Medium | |
| Area | Expedition | Conference | STACOM | ||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ PGM2012 | Serial | 1986 | ||
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| Author | Jose Carlos Rubio; Joan Serrat; Antonio Lopez; N. Paragios | ||||
| Title | Image Contextual Representation and Matching through Hierarchies and Higher Order Graphs | Type | Conference Article | ||
| Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 2664 - 2667 | ||
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| Abstract | We present a region matching algorithm which establishes correspondences between regions from two segmented images. An abstract graph-based representation conceals the image in a hierarchical graph, exploiting the scene properties at two levels. First, the similarity and spatial consistency of the image semantic objects is encoded in a graph of commute times. Second, the cluttered regions of the semantic objects are represented with a shape descriptor. Many-to-many matching of regions is specially challenging due to the instability of the segmentation under slight image changes, and we explicitly handle it through high order potentials. We demonstrate the matching approach applied to images of world famous buildings, captured under different conditions, showing the robustness of our method to large variations in illumination and viewpoint. | ||||
| Address | Tsukuba Science City, Japan | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1051-4651 | ISBN | 978-1-4673-2216-4 | Medium | |
| Area | Expedition | Conference | ICPR | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ RSL2012a; | Serial | 2032 | ||
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| Author | Debora Gil;Agnes Borras;Ruth Aris;Mariano Vazquez;Pierre Lafortune; Guillame Houzeaux | ||||
| Title | What a difference in biomechanics cardiac fiber makes | Type | Conference Article | ||
| Year | 2012 | Publication | Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges | Abbreviated Journal | |
| Volume | 7746 | Issue | Pages | 253-260 | |
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| Abstract | Computational simulations of the heart are a powerful tool for a comprehensive understanding of cardiac function and its intrinsic relationship with its muscular architecture. Cardiac biomechanical models require a vector field representing the orientation of cardiac fibers. A wrong orientation of the fibers can lead to a
non-realistic simulation of the heart functionality. In this paper we explore the impact of the fiber information on the simulated biomechanics of cardiac muscular anatomy. We have used the John Hopkins database to perform a biomechanical simulation using both a synthetic benchmark fiber distribution and the data obtained experimentally from DTI. Results illustrate how differences in fiber orientation affect heart deformation along cardiac cycle. |
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| Address | Nice, France | ||||
| Corporate Author | Thesis | ||||
| 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 | 978-3-642-36960-5 | Medium | |
| Area | Expedition | Conference | STACOM | ||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ GBA2012 | Serial | 1987 | ||
| Permanent link to this record | |||||
| Author | Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil | ||||
| Title | A medial map capturing the essential geometry of organs | Type | Conference Article | ||
| Year | 2012 | Publication | ISBI Workshop on Open Source Medical Image Analysis software | Abbreviated Journal | |
| Volume | Issue | Pages | 1691 - 1694 | ||
| Keywords | Medial Surface Representation, Volume Reconstruction,Geometry , Image reconstruction , Liver , Manifolds , Shape , Surface morphology , Surface reconstruction | ||||
| Abstract | Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Accurate computation of one pixel wide medial surfaces is mandatory. Those surfaces must represent faithfully the geometry of the volume. Although morphological methods produce excellent results in 2D, their complexity and quality drops across dimensions, due to a more complex description of pixel neighborhoods. This paper introduces a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. Our experiments show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume | ||||
| Address | Barcelona,Spain | ||||
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| Publisher | IEEE | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| ISSN | 1945-7928 | ISBN | 978-1-4577-1857-1 | Medium | |
| Area | Expedition | Conference | ISBI | ||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ VGG2012a | Serial | 1989 | ||
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