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Author | Enric Marti; Jordi Vitria; Alberto Sanfeliu | ||||
Title | Reconocimiento de Formas y Análisis de Imágenes | Type | Book Whole | ||
Year | 1998 | Publication | Asociación Española de Reconocimientos de Formas y Análisis de Imágenes | Abbreviated Journal | |
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Abstract | Los sistemas actuales de reconocimiento automático del lenguaje oral se basan en dos etapas básicas de procesado: la parametrización, que extrae la evolución temporal de los parámetros que caracterizan la voz, y el reconocimiento propiamente dicho, que identifica la cadena de palabras de la elocución recibida con ayuda de los modelos que representan el conocimiento adquirido en la etapa de aprendizaje. Tomando como línea divisoria la palabra, dichos modelos son de tipo acústicofonético o gramatical. Los primeros caracterizan las palabras incluidas en el vocabulario de la aplicación o tarea a la que está orientado el sistema de reconocimiento, usando a menudo para ello modelos de unidades de habla de extensión inferior a la palabra, es decir, de unidades subléxicas. Por otro lado, la gramática incluye el conocimiento acerca de las combinaciones permitidas de palabras para formar las frases o su probabilidad. Queda fuera del esquema la denominada comprensión del habla, que utiliza adicionalmente el conocimiento semántico y pragmático para captar el significado de la elocución de entrada al sistema a partir de la cadena (o cadenas alternativas) de palabras que suministra el reconocedor. | ||||
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Publisher | AERFAI | Place of Publication | Editor | ||
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ISSN | ISBN | 84–922529–4–4 | Medium | ||
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Notes | IAM;OR;MV | Approved | no | ||
Call Number | IAM @ iam @ MVS1998 | Serial | 1620 | ||
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Author | Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva | ||||
Title | Traffic-Sign Recognition Systems | Type | Book Whole | ||
Year | 2011 | Publication | SpringerBriefs in Computer Science | Abbreviated Journal | |
Volume | Issue | Pages | 5-13 | ||
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Publisher | Springer London | Place of Publication | Editor | ||
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ISSN | ISBN | 978-1-4471-2244-9 | Medium | ||
Area | Expedition | Conference | |||
Notes | MILAB; OR;HuPBA;MV | Approved | no | ||
Call Number | Admin @ si @ EBP2011 | Serial | 1801 | ||
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Author | David Geronimo; Antonio Lopez | ||||
Title | Vision-based Pedestrian Protection Systems for Intelligent Vehicles | Type | Book Whole | ||
Year | 2014 | Publication | SpringerBriefs in Computer Science | Abbreviated Journal | |
Volume | Issue | Pages | 1-114 | ||
Keywords | Computer Vision; Driver Assistance Systems; Intelligent Vehicles; Pedestrian Detection; Vulnerable Road Users | ||||
Abstract | Pedestrian Protection Systems (PPSs) are on-board systems aimed at detecting and tracking people in the surroundings of a vehicle in order to avoid potentially dangerous situations. These systems, together with other Advanced Driver Assistance Systems (ADAS) such as lane departure warning or adaptive cruise control, are one of the most promising ways to improve traffic safety. By the use of computer vision, cameras working either in the visible or infra-red spectra have been demonstrated as a reliable sensor to perform this task. Nevertheless, the variability of human’s appearance, not only in terms of clothing and sizes but also as a result of their dynamic shape, makes pedestrians one of the most complex classes even for computer vision. Moreover, the unstructured changing and unpredictable environment in which such on-board systems must work makes detection a difficult task to be carried out with the demanded robustness. In this brief, the state of the art in PPSs is introduced through the review of the most relevant papers of the last decade. A common computational architecture is presented as a framework to organize each method according to its main contribution. More than 300 papers are referenced, most of them addressing pedestrian detection and others corresponding to the descriptors (features), pedestrian models, and learning machines used. In addition, an overview of topics such as real-time aspects, systems benchmarking and future challenges of this research area are presented. | ||||
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Publisher | Springer Briefs in Computer Vision | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | 978-1-4614-7986-4 | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | GeL2014 | Serial | 2325 | ||
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Author | Angel Sappa; George A. Triantafyllid | ||||
Title | Computer Graphics and Imaging | Type | Book Whole | ||
Year | 2012 | Publication | Computer Graphics and Imaging | Abbreviated Journal | |
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Address | Crete, Greece | ||||
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ISSN | ISBN | 978-0-88986-921-9 | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ Sap2012 | Serial | 2067 | ||
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Author | Theo Gevers; Arjan Gijsenij; Joost Van de Weijer; J.M. Geusebroek | ||||
Title | Color in Computer Vision: Fundamentals and Applications | Type | Book Whole | ||
Year | 2012 | Publication | Color in Computer Vision: Fundamentals and Applications | Abbreviated Journal | |
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Publisher | The Wiley-IS&T Series in Imaging Science and Technology | Place of Publication | Editor | ||
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ISSN | ISBN | 978-0-470-89084-4 | Medium | ||
Area | Expedition | Conference | |||
Notes | ALTRES;ISE | Approved | no | ||
Call Number | Admin @ si @ GGG2012a | Serial | 2068 | ||
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Author | Mario Hernandez; Joao Sanchez; Jordi Vitria | ||||
Title | Selected papers from Iberian Conference on Pattern Recognition and Image Analysis | Type | Book Whole | ||
Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | |
Volume | 45 | Issue | 9 | Pages | 3047-3582 |
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ISSN | 0031-3203 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ HSV2012 | Serial | 2069 | ||
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Author | Angel Sappa; Jordi Vitria | ||||
Title | Multimodal Interaction in Image and Video Applications | Type | Book Whole | ||
Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications | Abbreviated Journal | |
Volume | 48 | Issue | Pages | ||
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Abstract | Book Series Intelligent Systems Reference Library | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
Area | Expedition | Conference | |||
Notes | ADAS; OR;MV | Approved | no | ||
Call Number | Admin @ si @ SaV2013 | Serial | 2199 | ||
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Author | Katerine Diaz; Francesc J. Ferri | ||||
Title | Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes | Type | Book Whole | ||
Year | 2013 | Publication | Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes | Abbreviated Journal | |
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Abstract | Los métodos basados en subespacios son una herramienta muy utilizada en aplicaciones de visión por computador. Aquí se presentan y validan algunos algoritmos que hemos propuesto en este campo de investigación. El primer algoritmo está relacionado con una extensión del método de vectores comunes discriminantes con kernel, que reinterpreta el espacio nulo de la matriz de dispersión intra-clase del conjunto de entrenamiento para obtener las características discriminantes. Dentro de los métodos basados en subespacios existen diferentes tipos de entrenamiento. Uno de los más populares, pero no por ello uno de los más eficientes, es el aprendizaje por lotes. En este tipo de aprendizaje, todas las muestras del conjunto de entrenamiento tienen que estar disponibles desde el inicio. De este modo, cuando nuevas muestras se ponen a disposición del algoritmo, el sistema tiene que ser reentrenado de nuevo desde cero. Una alternativa a este tipo de entrenamiento es el aprendizaje incremental. Aquí se proponen diferentes algoritmos incrementales del método de vectores comunes discriminantes. | ||||
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Publisher | Place of Publication | Editor | |||
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ISSN | ISBN | 978-3-639-55339-0 | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ DiF2013 | Serial | 2440 | ||
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Author | Simone Balocco; Maria Zuluaga; Guillaume Zahnd; Su-Lin Lee; Stefanie Demirci | ||||
Title | Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting | Type | Book Whole | ||
Year | 2016 | Publication | Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting | Abbreviated Journal | |
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Publisher | Elsevier | Place of Publication | Editor | ||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 9780128110188 | Medium | ||
Area | Expedition | Conference | |||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ BZZ2016 | Serial | 2821 | ||
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Author | Antonio Lopez; Atsushi Imiya; Tomas Pajdla; Jose Manuel Alvarez | ||||
Title | Computer Vision in Vehicle Technology: Land, Sea & Air | Type | Book Whole | ||
Year | 2017 | Publication | Abbreviated Journal | ||
Volume | Issue | Pages | 161-163 | ||
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Abstract | Summary This chapter examines different vision-based commercial solutions for real-live problems related to vehicles. It is worth mentioning the recent astonishing performance of deep convolutional neural networks (DCNNs) in difficult visual tasks such as image classification, object recognition/localization/detection, and semantic segmentation. In fact,
different DCNN architectures are already being explored for low-level tasks such as optical flow and disparity computation, and higher level ones such as place recognition. |
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Publisher | John Wiley & Sons, Ltd | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | 978-1-118-86807-2 | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS; 600.118 | Approved | no | ||
Call Number | Admin @ si @ LIP2017a | Serial | 2937 | ||
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Author | Laura Igual; Santiago Segui | ||||
Title | Introduction to Data Science – A Python Approach to Concepts, Techniques and Applications. Undergraduate Topics in Computer Science | Type | Book Whole | ||
Year | 2017 | Publication | Abbreviated Journal | ||
Volume | Issue | Pages | 1-215 | ||
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Publisher | 978-3-319-50016-4 | Place of Publication | Editor | ||
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ISSN | ISBN | 978-3-319-50016-4 | Medium | ||
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ IgS2017 | Serial | 3027 | ||
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Author | Antonio Lopez; Atsushi Imiya; Tomas Pajdla; Jose Manuel Alvarez | ||||
Title | Computer Vision in Vehicle Technology: Land, Sea & Air | Type | Book Whole | ||
Year | Publication | Computer Vision in Vehicle Technology: Land, Sea & Air | Abbreviated Journal | ||
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Abstract | A unified view of the use of computer vision technology for different types of vehicles
Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment). The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed. |
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ISSN | ISBN | 978-1-118-86807-2 | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ LIP2017b | Serial | 3049 | ||
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Author | Alicia Fornes; Bart Lamiroy | ||||
Title | Graphics Recognition, Current Trends and Evolutions | Type | Book Whole | ||
Year | 2018 | Publication | Graphics Recognition, Current Trends and Evolutions | Abbreviated Journal | |
Volume | 11009 | Issue | Pages | ||
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Abstract | This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Workshop on Graphics Recognition, GREC 2017, held in Kyoto, Japan, in November 2017.
The 10 revised full papers presented were carefully reviewed and selected from 14 initial submissions. They contain both classical and emerging topics of graphics rcognition, namely analysis and detection of diagrams, search and classification, optical music recognition, interpretation of engineering drawings and maps. |
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Publisher | Springer International Publishing | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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ISSN | ISBN | 978-3-030-02283-9 | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG; 600.121 | Approved | no | ||
Call Number | Admin @ si @ FoL2018 | Serial | 3171 | ||
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Author | Gholamreza Anbarjafari; Sergio Escalera | ||||
Title | Human-Robot Interaction: Theory and Application | Type | Book Whole | ||
Year | 2018 | Publication | Human-Robot Interaction: Theory and Application | Abbreviated Journal | |
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ISSN | ISBN | 978-1-78923-316-2 | Medium | ||
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Notes | HUPBA | Approved | no | ||
Call Number | Admin @ si @ AnE2018 | Serial | 3216 | ||
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Author | Sergio Escalera; Stephane Ayache; Jun Wan; Meysam Madadi; Umut Guçlu; Xavier Baro | ||||
Title | Inpainting and Denoising Challenges | Type | Book Whole | ||
Year | 2019 | Publication | The Springer Series on Challenges in Machine Learning | Abbreviated Journal | |
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Abstract | The problem of dealing with missing or incomplete data in machine learning and computer vision arises in many applications. Recent strategies make use of generative models to impute missing or corrupted data. Advances in computer vision using deep generative models have found applications in image/video processing, such as denoising, restoration, super-resolution, or inpainting.
Inpainting and Denoising Challenges comprises recent efforts dealing with image and video inpainting tasks. This includes winning solutions to the ChaLearn Looking at People inpainting and denoising challenges: human pose recovery, video de-captioning and fingerprint restoration. This volume starts with a wide review on image denoising, retracing and comparing various methods from the pioneer signal processing methods, to machine learning approaches with sparse and low-rank models, and recent deep learning architectures with autoencoders and variants. The following chapters present results from the Challenge, including three competition tasks at WCCI and ECML 2018. The top best approaches submitted by participants are described, showing interesting contributions and innovating methods. The last two chapters propose novel contributions and highlight new applications that benefit from image/video inpainting. |
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Notes | HUPBA; no menciona | Approved | no | ||
Call Number | Admin @ si @ EAW2019 | Serial | 3398 | ||
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