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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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| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | Jorge Bernal; David Vazquez | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| 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 | David Geronimo | ||||
| Title | A Global Approach to Vision-Based Pedestrian Detection for Advanced Driver Assistance Systems | Type | Book Whole | ||
| Year | 2010 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | At the beginning of the 21th century, traffic accidents have become a major problem not only for developed countries but also for emerging ones. As in other scientific areas in which Artificial Intelligence is becoming a key actor, advanced driver assistance systems, and concretely pedestrian protection systems based on Computer Vision, are becoming a strong topic of research aimed at improving the safety of pedestrians. However, the challenge is of considerable complexity due to the varying appearance of humans (e.g., clothes, size, aspect ratio, shape, etc.), the dynamic nature of on-board systems and the unstructured moving environments that urban scenarios represent. In addition, the required performance is demanding both in terms of computational time and detection rates. In this thesis, instead of focusing on improving specific tasks as it is frequent in the literature, we present a global approach to the problem. Such a global overview starts by the proposal of a generic architecture to be used as a framework both to review the literature and to organize the studied techniques along the thesis. We then focus the research on tasks such as foreground segmentation, object classification and refinement following a general viewpoint and exploring aspects that are not usually analyzed. In order to perform the experiments, we also present a novel pedestrian dataset that consists of three subsets, each one addressed to the evaluation of a different specific task in the system. The results presented in this thesis not only end with a proposal of a pedestrian detection system but also go one step beyond by pointing out new insights, formalizing existing and proposed algorithms, introducing new techniques and evaluating their performance, which we hope will provide new foundations for future research in the area. | ||||
| Address | Antonio Lopez;Krystian Mikolajczyk;Jaume Amores;Dariu M. Gavrila;Oriol Pujol;Felipe Lumbreras | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Antonio Lopez;Krystian Mikolajczyk;Jaume Amores;Dariu M. Gavrila;Oriol Pujol;Felipe Lumbreras | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-936529-5-1 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ Ger2010 | Serial | 1279 | ||
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| Author | Antonio Lopez | ||||
| Title | Multilocal Methods for Ridge and Valley Delineation in Image Analysis. | Type | Book Whole | ||
| Year | 2000 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Place of Publication | Editor | Joan Serrat | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
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| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ Lop2000 | Serial | 174 | ||
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| Author | Felipe Lumbreras | ||||
| Title | Segmentation, classification and modelization of textures by means of multiresolution decomposition techniques. | Type | Book Whole | ||
| Year | 2001 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ Lum2001 | Serial | 188 | ||
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| Author | Joan Marti; Jose Miguel Benedi; Ana Maria Mendonça; Joan Serrat | ||||
| Title | Pattern Recognition and Image Analysis | Type | Book Whole | ||
| Year | 2007 | Publication | 3rd Iberian Conference | Abbreviated Journal | |
| Volume | 6669 | Issue | Pages | 4477-4478 | |
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| Address | Girona (Spain) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | IbPRIA | ||
| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ MBM2007 | Serial | 994 | ||
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| Author | Daniel Ponsa | ||||
| Title | Model-Based Visual Localisation of Contours and Vehicles | Type | Book Whole | ||
| Year | 2007 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Phd Thesis | ||||
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| Address | |||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Antonio Lopez;Xavier Roca | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-935251-3-2 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ Pon2007 | Serial | 1107 | ||
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| Author | Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis | ||||
| Title | 3D Human Walking Modelling | Type | Book Whole | ||
| Year | 2004 | Publication | Articulated Motion and Deformable Objects, Third International Workshop, (AMDO 2004), Lecture Notes in Computer Science, F.J. Perales, B.A. Draper (Eds.), 3179:111–122 | Abbreviated Journal | |
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| Address | Springer-Verlag, Berlin, Heidelberg | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
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| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number |
ADAS @ adas @ SAM2004b | Serial | 494 | ||
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| Author | Angel Sappa (ed) | ||||
| Title | Computer Graphics and Imaging | Type | Book Whole | ||
| Year | 2010 | Publication | Computer Graphics and Imaging | Abbreviated Journal | |
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| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | Angel Sappa | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978–0–88986–836–6 | Medium | ||
| Area | Expedition | Conference | CGIM | ||
| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ Sap2010 | Serial | 1468 | ||
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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 | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-940530-1-6 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | adas | Approved | yes | ||
| Call Number |
ADAS @ adas @ Vaz2013 | Serial | 2276 | ||
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| Author | Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) | ||||
| Title | 16th International Conference, 2021, Proceedings, Part III | Type | Book Whole | ||
| Year | 2021 | Publication | Document Analysis and Recognition – ICDAR 2021 | Abbreviated Journal | |
| Volume | 12823 | Issue | Pages | ||
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| Abstract | This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
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| Address | Lausanne, Switzerland, September 5-10, 2021 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Cham | Place of Publication | Editor | Josep Llados; Daniel Lopresti; Seiichi Uchida | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-030-86333-3 | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG | Approved | no | ||
| Call Number |
Admin @ si @ | Serial | 3727 | ||
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| Author | Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) | ||||
| Title | 16th International Conference, 2021, Proceedings, Part IV | Type | Book Whole | ||
| Year | 2021 | Publication | Document Analysis and Recognition – ICDAR 2021 | Abbreviated Journal | |
| Volume | 12824 | Issue | Pages | ||
| Keywords | |||||
| Abstract | This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
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| Address | Lausanne, Switzerland, September 5-10, 2021 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Cham | Place of Publication | Editor | Josep Llados; Daniel Lopresti; Seiichi Uchida | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-030-86336-4 | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG | Approved | no | ||
| Call Number |
Admin @ si @ | Serial | 3728 | ||
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| Author | Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) | ||||
| Title | 16th International Conference, 2021, Proceedings, Part I | Type | Book Whole | ||
| Year | 2021 | Publication | Document Analysis and Recognition – ICDAR 2021 | Abbreviated Journal | |
| Volume | 12821 | Issue | Pages | ||
| Keywords | |||||
| Abstract | This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: historical document analysis, document analysis systems, handwriting recognition, scene text detection and recognition, document image processing, natural language processing (NLP) for document understanding, and graphics, diagram and math recognition. |
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| Address | Lausanne, Switzerland, September 5-10, 2021 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Cham | Place of Publication | Editor | Josep Llados; Daniel Lopresti; Seiichi Uchida | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-030-86548-1 | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG | Approved | no | ||
| Call Number |
Admin @ si @ | Serial | 3725 | ||
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| Author | Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) | ||||
| Title | 16th International Conference, 2021, Proceedings, Part II | Type | Book Whole | ||
| Year | 2021 | Publication | Document Analysis and Recognition – ICDAR 2021 | Abbreviated Journal | |
| Volume | 12822 | Issue | Pages | ||
| Keywords | |||||
| Abstract | This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
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| Address | Lausanne, Switzerland, September 5-10, 2021 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Cham | Place of Publication | Editor | Josep Llados; Daniel Lopresti; Seiichi Uchida | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-030-86330-2 | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG | Approved | no | ||
| Call Number |
Admin @ si @ | Serial | 3726 | ||
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| Author | Cristhian Aguilera | ||||
| Title | Local feature description in cross-spectral imagery | Type | Book Whole | ||
| Year | 2017 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Over the last few years, the number of consumer computer vision applications has increased dramatically. Today, computer vision solutions can be found in video game consoles, smartphone applications, driving assistance – just to name a few. Ideally, we require the performance of those applications, particularly those that are safety critical to remain constant under any external environment factors, such as changes in illumination or weather conditions. However, this is not always possible or very difficult to obtain by only using visible imagery, due to the inherent limitations of the images from that spectral band. For that reason, the use of images from different or multiple spectral bands is becoming more appealing.
The aforementioned possible advantages of using images from multiples spectral bands on various vision applications make multi-spectral image processing a relevant topic for research and development. Like in visible image processing, multi-spectral image processing needs tools and algorithms to handle information from various spectral bands. Furthermore, traditional tools such as local feature detection, which is the basis of many vision tasks such as visual odometry, image registration, or structure from motion, must be adjusted or reformulated to operate under new conditions. Traditional feature detection, description, and matching methods tend to underperform in multi-spectral settings, in comparison to mono-spectral settings, due to the natural differences between each spectral band. The work in this thesis is focused on the local feature description problem when cross-spectral images are considered. In this context, this dissertation has three main contributions. Firstly, the work starts by proposing the usage of a combination of frequency and spatial information, in a multi-scale scheme, as feature description. Evaluations of this proposal, based on classical hand-made feature descriptors, and comparisons with state of the art cross-spectral approaches help to find and understand limitations of such strategy. Secondly, different convolutional neural network (CNN) based architectures are evaluated when used to describe cross-spectral image patches. Results showed that CNN-based methods, designed to work with visible monocular images, could be successfully applied to the description of images from two different spectral bands, with just minor modifications. In this framework, a novel CNN-based network model, specifically intended to describe image patches from two different spectral bands, is proposed. This network, referred to as Q-Net, outperforms state of the art in the cross-spectral domain, including both previous hand-made solutions as well as L2 CNN-based architectures. The third contribution of this dissertation is in the cross-spectral feature description application domain. The multispectral odometry problem is tackled showing a real application of cross-spectral descriptors In addition to the three main contributions mentioned above, in this dissertation, two different multi-spectral datasets are generated and shared with the community to be used as benchmarks for further studies. |
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| Address | October 2017 | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Angel Sappa | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-945373-6-3 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS; 600.118 | Approved | no | ||
| Call Number |
Admin @ si @ Agu2017 | Serial | 3020 | ||
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| Author | Arash Akbarinia | ||||
| Title | Computational Model of Visual Perception: From Colour to Form | Type | Book Whole | ||
| Year | 2017 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | The original idea of this project was to study the role of colour in the challenging task of object recognition. We started by extending previous research on colour naming showing that it is feasible to capture colour terms through parsimonious ellipsoids. Although, the results of our model exceeded state-of-the-art in two benchmark datasets, we realised that the two phenomena of metameric lights and colour constancy must be addressed prior to any further colour processing. Our investigation of metameric pairs reached the conclusion that they are infrequent in real world scenarios. Contrary to that, the illumination of a scene often changes dramatically. We addressed this issue by proposing a colour constancy model inspired by the dynamical centre-surround adaptation of neurons in the visual cortex. This was implemented through two overlapping asymmetric Gaussians whose variances and heights are adjusted according to the local contrast of pixels. We complemented this model with a generic contrast-variant pooling mechanism that inversely connect the percentage of pooled signal to the local contrast of a region. The results of our experiments on four benchmark datasets were indeed promising: the proposed model, although simple, outperformed even learning-based approaches in many cases. Encouraged by the success of our contrast-variant surround modulation, we extended this approach to detect boundaries of objects. We proposed an edge detection model based on the first derivative of the Gaussian kernel. We incorporated four types of surround: full, far, iso- and orthogonal-orientation. Furthermore, we accounted for the pooling mechanism at higher cortical areas and the shape feedback sent to lower areas. Our results in three benchmark datasets showed significant improvement over non-learning algorithms.
To summarise, we demonstrated that biologically-inspired models offer promising solutions to computer vision problems, such as, colour naming, colour constancy and edge detection. We believe that the greatest contribution of this Ph.D dissertation is modelling the concept of dynamic surround modulation that shows the significance of contrast-variant surround integration. The models proposed here are grounded on only a portion of what we know about the human visual system. Therefore, it is only natural to complement them accordingly in future works. |
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| Address | October 2017 | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | C. Alejandro Parraga | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-945373-4-9 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | NEUROBIT | Approved | no | ||
| Call Number |
Admin @ si @ Akb2017 | Serial | 3019 | ||
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