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| Author | Bogdan Raducanu; Fadi Dornaika | ||||
| Title | A Discriminative Non-Linear Manifold Learning Technique for Face Recognition | Type | Book Chapter | ||
| Year | 2011 | Publication  |
Informatics Engineering and Information Science | Abbreviated Journal | |
| Volume | 254 | Issue | 6 | Pages | 339-353 |
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| Abstract | In this paper we propose a novel non-linear discriminative analysis technique for manifold learning. The proposed approach is a discriminant version of Laplacian Eigenmaps which takes into account the class label information in order to guide the procedure of non-linear dimensionality reduction. By following the large margin concept, the graph Laplacian is split in two components: within-class graph and between-class graph to better characterize the discriminant property of the data.
Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques. The experimental results confirm that our method outperforms, in general, the existing ones. Although we have concentrated in this paper on the face recognition problem, the proposed approach could also be applied to other category of objects characterized by large variance in their appearance. |
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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 | 1865-0929 | ISBN | 978-3-642-25482-6 | Medium | |
| Area | Expedition | Conference | ICIEIS | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ RaD2011 | Serial | 1804 | ||
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| Author | Angel Sappa; Boris X. Vintimilla | ||||
| Title | Edge Point Linking by Means of Global and Local Schemes | Type | Book Chapter | ||
| Year | 2008 | Publication |
in Signal Processing for Image Enhancement and Multimedia Processing | Abbreviated Journal | |
| Volume | 11 | Issue | Pages | 115–125 | |
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| Publisher | Springer | Place of Publication | Editor | E. Damiani | |
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ SaV2008 | Serial | 938 | ||
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| Author | David Guillamet; Jordi Vitria | ||||
| Title | An Experimental Evaluation of K-nn for Linear Transforms of Positive Data | Type | Book Chapter | ||
| Year | 2003 | Publication |
In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science. 2652:317–325 | Abbreviated Journal | |
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| Address | Springer-Verlag | ||||
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| Area | Expedition | Conference | |||
| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ GuV2003a | Serial | 379 | ||
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| Author | Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil | ||||
| Title | An illumination model of the trachea appearance in videobronchoscopy images | Type | Book Chapter | ||
| Year | 2012 | Publication |
Image Analysis and Recognition | Abbreviated Journal | LNCS |
| Volume | 7325 | Issue | Pages | 313-320 | |
| Keywords | Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation | ||||
| Abstract | Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution. |
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| Address | Aveiro, Portugal | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Lecture Notes in Computer Science | Abbreviated Series Title | LNCS | |
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-31297-7 | Medium | |
| Area | 800 | Expedition | Conference | ICIAR | |
| Notes | MV;IAM | Approved | no | ||
| Call Number | IAM @ iam @ SSR2012 | Serial | 1898 | ||
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| Author | Jorge Charco; Angel Sappa; Boris X. Vintimilla; Henry Velesaca | ||||
| Title | Human Body Pose Estimation in Multi-view Environments | Type | Book Chapter | ||
| Year | 2022 | Publication |
ICT Applications for Smart Cities. Intelligent Systems Reference Library | Abbreviated Journal | |
| Volume | 224 | Issue | Pages | 79-99 | |
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| Abstract | This chapter tackles the challenging problem of human pose estimation in multi-view environments to handle scenes with self-occlusions. The proposed approach starts by first estimating the camera pose—extrinsic parameters—in multi-view scenarios; due to few real image datasets, different virtual scenes are generated by using a special simulator, for training and testing the proposed convolutional neural network based approaches. Then, these extrinsic parameters are used to establish the relation between different cameras into the multi-view scheme, which captures the pose of the person from different points of view at the same time. The proposed multi-view scheme allows to robustly estimate human body joints’ position even in situations where they are occluded. This would help to avoid possible false alarms in behavioral analysis systems of smart cities, as well as applications for physical therapy, safe moving assistance for the elderly among other. The chapter concludes by presenting experimental results in real scenes by using state-of-the-art and the proposed multi-view approaches. | ||||
| Address | September 2022 | ||||
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| Publisher | Springer | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | ISRL | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-031-06306-0 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MSIAU; MACO | Approved | no | ||
| Call Number | Admin @ si @ CSV2022b | Serial | 3810 | ||
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| Author | Victoria Ruiz; Angel Sanchez; Jose F. Velez; Bogdan Raducanu | ||||
| Title | Waste Classification with Small Datasets and Limited Resources | Type | Book Chapter | ||
| Year | 2022 | Publication |
ICT Applications for Smart Cities. Intelligent Systems Reference Library | Abbreviated Journal | |
| Volume | 224 | Issue | Pages | 185-203 | |
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| Abstract | Automatic waste recycling has become a very important societal challenge nowadays, raising people’s awareness for a cleaner environment and a more sustainable lifestyle. With the transition to Smart Cities, and thanks to advanced ICT solutions, this problem has received a new impulse. The waste recycling focus has shifted from general waste treating facilities to an individual responsibility, where each person should become aware of selective waste separation. The surge of the mobile devices, accompanied by a significant increase in computation power, has potentiated and facilitated this individual role. An automated image-based waste classification mechanism can help with a more efficient recycling and a reduction of contamination from residuals. Despite the good results achieved with the deep learning methodologies for this task, the Achille’s heel is that they require large neural networks which need significant computational resources for training and therefore are not suitable for mobile devices. To circumvent this apparently intractable problem, we will rely on knowledge distillation in order to transfer the network’s knowledge from a larger network (called ‘teacher’) to a smaller, more compact one, (referred as ‘student’) and thus making it possible the task of image classification on a device with limited resources. For evaluation, we considered as ‘teachers’ large architectures such as InceptionResNet or DenseNet and as ‘students’, several configurations of the MobileNets. We used the publicly available TrashNet dataset to demonstrate that the distillation process does not significantly affect system’s performance (e.g. classification accuracy) of the student network. | ||||
| Address | September 2022 | ||||
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| Publisher | Springer | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | ISRL | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-031-06306-0 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | LAMP | Approved | no | ||
| Call Number | Admin @ si @ | Serial | 3813 | ||
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| Author | Henry Velesaca; Patricia Suarez; Dario Carpio; Rafael E. Rivadeneira; Angel Sanchez; Angel Morera | ||||
| Title | Video Analytics in Urban Environments: Challenges and Approaches | Type | Book Chapter | ||
| Year | 2022 | Publication |
ICT Applications for Smart Cities | Abbreviated Journal | |
| Volume | 224 | Issue | Pages | 101-121 | |
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| Abstract | This chapter reviews state-of-the-art approaches generally present in the pipeline of video analytics on urban scenarios. A typical pipeline is used to cluster approaches in the literature, including image preprocessing, object detection, object classification, and object tracking modules. Then, a review of recent approaches for each module is given. Additionally, applications and datasets generally used for training and evaluating the performance of these approaches are included. This chapter does not pretend to be an exhaustive review of state-of-the-art video analytics in urban environments but rather an illustration of some of the different recent contributions. The chapter concludes by presenting current trends in video analytics in the urban scenario field. | ||||
| Address | September 2022 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | ISRL | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-031-06306-0 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MSIAU; MACO | Approved | no | ||
| Call Number | Admin @ si @ VSC2022 | Serial | 3811 | ||
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| Author | Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez | ||||
| Title | Exploiting Natural Language Generation in Scene Interpretation | Type | Book Chapter | ||
| Year | 2009 | Publication |
Human–Centric Interfaces for Ambient Intelligence | Abbreviated Journal | |
| Volume | 4 | Issue | Pages | 71–93 | |
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| Publisher | Elsevier Science and Tech | Place of Publication | Editor | ||
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| Notes | ISE | Approved | no | ||
| Call Number | ISE @ ise @ FBR2009 | Serial | 1212 | ||
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| Author | Rain Eric Haamer; Eka Rusadze; Iiris Lusi; Tauseef Ahmed; Sergio Escalera; Gholamreza Anbarjafari | ||||
| Title | Review on Emotion Recognition Databases | Type | Book Chapter | ||
| Year | 2018 | Publication |
Human-Robot Interaction: Theory and Application | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | emotion; computer vision; databases | ||||
| Abstract | Over the past few decades human-computer interaction has become more important in our daily lives and research has developed in many directions: memory research, depression detection, and behavioural deficiency detection, lie detection, (hidden) emotion recognition etc. Because of that, the number of generic emotion and face databases or those tailored to specific needs have grown immensely large. Thus, a comprehensive yet compact guide is needed to help researchers find the most suitable database and understand what types of databases already exist. In this paper, different elicitation methods are discussed and the databases are primarily organized into neat and informative tables based on the format. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-78923-316-2 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | HUPBA; 602.133 | Approved | no | ||
| Call Number | Admin @ si @ HRL2018 | Serial | 3212 | ||
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| Author | Alicia Fornes; Josep Llados; Joana Maria Pujadas-Mora | ||||
| Title | Browsing of the Social Network of the Past: Information Extraction from Population Manuscript Images | Type | Book Chapter | ||
| Year | 2020 | Publication |
Handwritten Historical Document Analysis, Recognition, and Retrieval – State of the Art and Future Trends | Abbreviated Journal | |
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| Publisher | World Scientific | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-981-120-323-7 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.140; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ FLP2020 | Serial | 3350 | ||
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| Author | Javier Marin; David Geronimo; David Vazquez; Antonio Lopez | ||||
| Title | Pedestrian Detection: Exploring Virtual Worlds | Type | Book Chapter | ||
| Year | 2012 | Publication |
Handbook of Pattern Recognition: Methods and Application | Abbreviated Journal | |
| Volume | 5 | Issue | Pages | 145-162 | |
| Keywords | Virtual worlds; Pedestrian Detection; Domain Adaptation | ||||
| Abstract | Handbook of pattern recognition will include contributions from university educators and active research experts. This Handbook is intended to serve as a basic reference on methods and applications of pattern recognition. The primary aim of this handbook is providing the community of pattern recognition with a readable, easy to understand resource that covers introductory, intermediate and advanced topics with equal clarity. Therefore, the Handbook of pattern recognition can serve equally well as reference resource and as classroom textbook. Contributions cover all methods, techniques and applications of pattern recognition. A tentative list of relevant topics might include: 1- Statistical, structural, syntactic pattern recognition. 2- Neural networks, machine learning, data mining. 3- Discrete geometry, algebraic, graph-based techniques for pattern recognition. 4- Face recognition, Signal analysis, image coding and processing, shape and texture analysis. 5- Document processing, text and graphics recognition, digital libraries. 6- Speech recognition, music analysis, multimedia systems. 7- Natural language analysis, information retrieval. 8- Biometrics, biomedical pattern analysis and information systems. 9- Other scientific, engineering, social and economical applications of pattern recognition. 10- Special hardware architectures, software packages for pattern recognition. | ||||
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| Publisher | iConcept Press | Place of Publication | Editor | ||
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-477554-82-1 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ MGV2012 | Serial | 1979 | ||
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| Author | Julie Digne; Mariella Dimiccoli; Neus Sabater; Philippe Salembier | ||||
| Title | Neighborhood Filters and the Recovery of 3D Information | Type | Book Chapter | ||
| Year | 2015 | Publication |
Handbook of Mathematical Methods in Imaging | Abbreviated Journal | |
| Volume | Issue | III | Pages | 1645-1673 | |
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| Abstract | Following their success in image processing (see Chapter Local Smoothing Neighborhood Filters), neighborhood filters have been extended to 3D surface processing. This adaptation is not straightforward. It has led to several variants for surfaces depending on whether the surface is defined as a mesh, or as a raw data point set. The image gray level in the bilateral similarity measure is replaced by a geometric information such as the normal or the curvature. The first section of this chapter reviews the variants of 3D mesh bilateral filters and compares them to the simplest possible isotropic filter, the mean curvature motion.In a second part, this chapter reviews applications of the bilateral filter to a data composed of a sparse depth map (or of depth cues) and of the image on which they have been computed. Such sparse depth cues can be obtained by stereovision or by psychophysical techniques. The underlying assumption to these applications is that pixels with similar intensity around a region are likely to have similar depths. Therefore, when diffusing depth information with a bilateral filter based on locality and color similarity, the discontinuities in depth are assured to be consistent with the color discontinuities, which is generally a desirable property. In the reviewed applications, this ends up with the reconstruction of a dense perceptual depth map from the joint data of an image and of depth cues. | ||||
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| Publisher | Springer New York | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-4939-0789-2 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ DDS2015 | Serial | 2710 | ||
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| Author | Josep Llados; Marçal Rusiñol | ||||
| Title | Graphics Recognition Techniques | Type | Book Chapter | ||
| Year | 2014 | Publication |
Handbook of Document Image Processing and Recognition | Abbreviated Journal | |
| Volume | D | Issue | Pages | 489-521 | |
| Keywords | Dimension recognition; Graphics recognition; Graphic-rich documents; Polygonal approximation; Raster-to-vector conversion; Texture-based primitive extraction; Text-graphics separation | ||||
| Abstract | This chapter describes the most relevant approaches for the analysis of graphical documents. The graphics recognition pipeline can be splitted into three tasks. The low level or lexical task extracts the basic units composing the document. The syntactic level is focused on the structure, i.e., how graphical entities are constructed, and involves the location and classification of the symbols present in the document. The third level is a functional or semantic level, i.e., it models what the graphical symbols do and what they mean in the context where they appear. This chapter covers the lexical level, while the next two chapters are devoted to the syntactic and semantic level, respectively. The main problems reviewed in this chapter are raster-to-vector conversion (vectorization algorithms) and the separation of text and graphics components. The research and industrial communities have provided standard methods achieving reasonable performance levels. Hence, graphics recognition techniques can be considered to be in a mature state from a scientific point of view. Additionally this chapter provides insights on some related problems, namely, the extraction and recognition of dimensions in engineering drawings, and the recognition of hatched and tiled patterns. Both problems are usually associated, even integrated, in the vectorization process. | ||||
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| Publisher | Springer London | Place of Publication | Editor | D. Doermann; K. Tombre | |
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-0-85729-858-4 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ LlR2014 | Serial | 2380 | ||
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| Author | Salvatore Tabbone; Oriol Ramos Terrades | ||||
| Title | An Overview of Symbol Recognition | Type | Book Chapter | ||
| Year | 2014 | Publication |
Handbook of Document Image Processing and Recognition | Abbreviated Journal | |
| Volume | D | Issue | Pages | 523-551 | |
| Keywords | Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting | ||||
| Abstract | According to the Cambridge Dictionaries Online, a symbol is a sign, shape, or object that is used to represent something else. Symbol recognition is a subfield of general pattern recognition problems that focuses on identifying, detecting, and recognizing symbols in technical drawings, maps, or miscellaneous documents such as logos and musical scores. This chapter aims at providing the reader an overview of the different existing ways of describing and recognizing symbols and how the field has evolved to attain a certain degree of maturity. | ||||
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| Publisher | Springer London | Place of Publication | Editor | D. Doermann; K. Tombre | |
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-0-85729-858-4 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ TaT2014 | Serial | 2489 | ||
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| Author | A.Kesidis; Dimosthenis Karatzas | ||||
| Title | Logo and Trademark Recognition | Type | Book Chapter | ||
| Year | 2014 | Publication |
Handbook of Document Image Processing and Recognition | Abbreviated Journal | |
| Volume | D | Issue | Pages | 591-646 | |
| Keywords | Logo recognition; Logo removal; Logo spotting; Trademark registration; Trademark retrieval systems | ||||
| Abstract | The importance of logos and trademarks in nowadays society is indisputable, variably seen under a positive light as a valuable service for consumers or a negative one as a catalyst of ever-increasing consumerism. This chapter discusses the technical approaches for enabling machines to work with logos, looking into the latest methodologies for logo detection, localization, representation, recognition, retrieval, and spotting in a variety of media. This analysis is presented in the context of three different applications covering the complete depth and breadth of state of the art techniques. These are trademark retrieval systems, logo recognition in document images, and logo detection and removal in images and videos. This chapter, due to the very nature of logos and trademarks, brings together various facets of document image analysis spanning graphical and textual content, while it links document image analysis to other computer vision domains, especially when it comes to the analysis of real-scene videos and images. | ||||
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| Publisher | Springer London | Place of Publication | Editor | D. Doermann; K. Tombre | |
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-0-85729-858-4 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ KeK2014 | Serial | 2425 | ||
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