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Author Bogdan Raducanu; Fadi Dornaika edit  doi
isbn  openurl
  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  
  Keywords (up)  
  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.
 
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  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  
Permanent link to this record
 

 
Author Nataliya Shapovalova; Carles Fernandez; Xavier Roca; Jordi Gonzalez edit  doi
isbn  openurl
  Title Semantics of Human Behavior in Image Sequences Type Book Chapter
  Year 2011 Publication Computer Analysis of Human Behavior Abbreviated Journal  
  Volume Issue 7 Pages 151-182  
  Keywords (up)  
  Abstract Human behavior is contextualized and understanding the scene of an action is crucial for giving proper semantics to behavior. In this chapter we present a novel approach for scene understanding. The emphasis of this work is on the particular case of Human Event Understanding. We introduce a new taxonomy to organize the different semantic levels of the Human Event Understanding framework proposed. Such a framework particularly contributes to the scene understanding domain by (i) extracting behavioral patterns from the integrative analysis of spatial, temporal, and contextual evidence and (ii) integrative analysis of bottom-up and top-down approaches in Human Event Understanding. We will explore how the information about interactions between humans and their environment influences the performance of activity recognition, and how this can be extrapolated to the temporal domain in order to extract higher inferences from human events observed in sequences of images.  
  Address  
  Corporate Author Thesis  
  Publisher Springer London Place of Publication Editor Albert Ali Salah;  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-0-85729-993-2 Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ SFR2011 Serial 1810  
Permanent link to this record
 

 
Author Murad Al Haj; Carles Fernandez; Zhanwu Xiong; Ivan Huerta; Jordi Gonzalez; Xavier Roca edit  doi
isbn  openurl
  Title Beyond the Static Camera: Issues and Trends in Active Vision Type Book Chapter
  Year 2011 Publication Visual Analysis of Humans: Looking at People Abbreviated Journal  
  Volume Issue 2 Pages 11-30  
  Keywords (up)  
  Abstract Maximizing both the area coverage and the resolution per target is highly desirable in many applications of computer vision. However, with a limited number of cameras viewing a scene, the two objectives are contradictory. This chapter is dedicated to active vision systems, trying to achieve a trade-off between these two aims and examining the use of high-level reasoning in such scenarios. The chapter starts by introducing different approaches to active cameras configurations. Later, a single active camera system to track a moving object is developed, offering the reader first-hand understanding of the issues involved. Another section discusses practical considerations in building an active vision platform, taking as an example a multi-camera system developed for a European project. The last section of the chapter reflects upon the future trends of using semantic factors to drive smartly coordinated active systems.  
  Address  
  Corporate Author Thesis  
  Publisher Springer London Place of Publication Editor Th.B. Moeslund; A. Hilton; V. Krüger; L. Sigal  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-0-85729-996-3 Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ AFX2011 Serial 1814  
Permanent link to this record
 

 
Author Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke edit  doi
openurl 
  Title Writer Identification in Old Handwritten Music Scores Type Book Chapter
  Year 2012 Publication Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology Abbreviated Journal  
  Volume Issue Pages 27-63  
  Keywords (up)  
  Abstract The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores. Even though an important amount of compositions contains handwritten text in the music scores, the aim of our work is to use only music notation to determine the author. The steps of the system proposed are the following. First of all, the music sheet is preprocessed and normalized for obtaining a single binarized music line, without the staff lines. Afterwards, 100 features are extracted for every music line, which are subsequently used in a k-NN classifier that compares every feature vector with prototypes stored in a database. By applying feature selection and extraction methods on the original feature set, the performance is increased. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving a recognition rate of about 95%.  
  Address  
  Corporate Author Thesis  
  Publisher IGI-Global Place of Publication Editor Copnstantin Papaodysseus  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ FLS2012 Serial 1828  
Permanent link to this record
 

 
Author Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva edit  url
doi  isbn
openurl 
  Title On the Design of Low Redundancy Error-Correcting Output Codes Type Book Chapter
  Year 2011 Publication Ensembles in Machine Learning Applications Abbreviated Journal  
  Volume 373 Issue 2 Pages 21-38  
  Keywords (up)  
  Abstract The classification of large number of object categories is a challenging trend in the Pattern Recognition field. In the literature, this is often addressed using an ensemble of classifiers . In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for combining classifiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a compact design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best compact ECOC code configuration. The results over several public UCI data sets and different multi-class Computer Vision problems show that the proposed methodology obtains comparable (even better) results than the state-of-the-art ECOC methodologies with far less number of dichotomizers.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1860-949X ISBN 978-3-642-22909-1 Medium  
  Area Expedition Conference  
  Notes MILAB; OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ BEB2011b Serial 1886  
Permanent link to this record
 

 
Author Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol edit   pdf
url  doi
isbn  openurl
  Title Interactive Document Retrieval and Classification. Type Book Chapter
  Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal  
  Volume 48 Issue Pages 17-30  
  Keywords (up)  
  Abstract In this chapter we describe a system for document retrieval and classification following the interactive-predictive framework. In particular, the system addresses two different scenarios of document analysis: document classification based on visual appearance and logo detection. These two classical problems of document analysis are formulated following the interactive-predictive model, taking the user interaction into account to make easier the process of annotating and labelling the documents. A system implementing this model in a real scenario is presented and analyzed. This system also takes advantage of active learning techniques to speed up the task of labelling the documents.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Angel Sappa; Jordi Vitria  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ VRM2013 Serial 2341  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny edit   pdf
doi  isbn
openurl 
  Title Notation-invariant patch-based wall detector in architectural floor plans Type Book Chapter
  Year 2013 Publication Graphics Recognition. New Trends and Challenges Abbreviated Journal  
  Volume 7423 Issue Pages 79--88  
  Keywords (up)  
  Abstract Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper.  
  Address  
  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 978-3-642-36823-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.045; 600.056; 605.203 Approved no  
  Call Number Admin @ si @ HMS2013 Serial 2322  
Permanent link to this record
 

 
Author Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana edit   pdf
doi  isbn
openurl 
  Title Interactive Visual and Semantic Image Retrieval Type Book Chapter
  Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal  
  Volume 48 Issue Pages 31-35  
  Keywords (up)  
  Abstract One direct consequence of recent advances in digital visual data generation and the direct availability of this information through the World-Wide Web, is a urgent demand for efficient image retrieval systems. The objective of image retrieval is to allow users to efficiently browse through this abundance of images. Due to the non-expert nature of the majority of the internet users, such systems should be user friendly, and therefore avoid complex user interfaces. In this chapter we investigate how high-level information provided by recently developed object recognition techniques can improve interactive image retrieval. Wel apply a bagof- word based image representation method to automatically classify images in a number of categories. These additional labels are then applied to improve the image retrieval system. Next to these high-level semantic labels, we also apply a low-level image description to describe the composition and color scheme of the scene. Both descriptions are incorporated in a user feedback image retrieval setting. The main objective is to show that automatic labeling of images with semantic labels can improve image retrieval results.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Angel Sappa; Jordi Vitria  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium  
  Area Expedition Conference  
  Notes CIC; 605.203; 600.048 Approved no  
  Call Number Admin @ si @ WKC2013 Serial 2284  
Permanent link to this record
 

 
Author Carles Fernandez; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca edit   pdf
doi  isbn
openurl 
  Title Towards Ontological Cognitive System Type Book Chapter
  Year 2013 Publication Topics in Medical Image Processing and Computational Vision Abbreviated Journal  
  Volume 8 Issue Pages 87-99  
  Keywords (up)  
  Abstract The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. This raises a series of technological demands for automatic video understanding and management, which together with the compromising attentional limitations of human operators, have motivated the research community to guide its steps towards a better attainment of such capabilities. As a result, current trends on cognitive vision promise to recognize complex events and self-adapt to different environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Netherlands Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2212-9391 ISBN 978-94-007-0725-2 Medium  
  Area Expedition Conference  
  Notes ISE; 605.203; 302.018; 600.049 Approved no  
  Call Number Admin @ si @ FGT2013 Serial 2287  
Permanent link to this record
 

 
Author Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados edit  url
doi  isbn
openurl 
  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  
  Keywords (up)  
  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.  
  Address  
  Corporate Author Thesis  
  Publisher Springer New York Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4614-4456-5 Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ LRL2013b Serial 2271  
Permanent link to this record
 

 
Author Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez edit   pdf
doi  isbn
openurl 
  Title Trajectory-Based Abnormality Categorization for Learning Route Patterns in Surveillance Type Book Chapter
  Year 2012 Publication Detection and Identification of Rare Audiovisual Cues, Studies in Computational Intelligence Abbreviated Journal  
  Volume 384 Issue 3 Pages 87-95  
  Keywords (up)  
  Abstract The recognition of abnormal behaviors in video sequences has raised as a hot topic in video understanding research. Particularly, an important challenge resides on automatically detecting abnormality. However, there is no convention about the types of anomalies that training data should derive. In surveillance, these are typically detected when new observations differ substantially from observed, previously learned behavior models, which represent normality. This paper focuses on properly defining anomalies within trajectory analysis: we propose a hierarchical representation conformed by Soft, Intermediate, and Hard Anomaly, which are identified from the extent and nature of deviation from learned models. Towards this end, a novel Gaussian Mixture Model representation of learned route patterns creates a probabilistic map of the image plane, which is applied to detect and classify anomalies in real-time. Our method overcomes limitations of similar existing approaches, and performs correctly even when the tracking is affected by different sources of noise. The reliability of our approach is demonstrated experimentally.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1860-949X ISBN 978-3-642-24033-1 Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ BFR2012 Serial 2062  
Permanent link to this record
 

 
Author Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus edit   pdf
openurl 
  Title Color Naming Type Book Chapter
  Year 2012 Publication Color in Computer Vision: Fundamentals and Applications Abbreviated Journal  
  Volume Issue 17 Pages 287-317  
  Keywords (up)  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher John Wiley & Sons, Ltd. Place of Publication Editor Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number Admin @ si @ WBV2012 Serial 2063  
Permanent link to this record
 

 
Author Xavier Perez Sala; Laura Igual; Sergio Escalera; Cecilio Angulo edit   pdf
doi  openurl
  Title Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models Type Book Chapter
  Year 2012 Publication Vision Robotics: Technologies for Machine Learning and Vision Applications Abbreviated Journal  
  Volume Issue 2 Pages 23-42  
  Keywords (up)  
  Abstract Different methodologies of uniform sampling over the rotation group, SO(3), for building unbiased 2D shape models from 3D objects are introduced and reviewed in this chapter. State-of-the-art non uniform sampling approaches are discussed, and uniform sampling methods using Euler angles and quaternions are introduced. Moreover, since presented work is oriented to model building applications, it is not limited to general discrete methods to obtain uniform 3D rotations, but also from a continuous point of view in the case of Procrustes Analysis.  
  Address  
  Corporate Author Thesis  
  Publisher IGI-Global Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ PIE2012 Serial 2064  
Permanent link to this record
 

 
Author Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Oscar Vilarroya; Petia Radeva edit  url
isbn  openurl
  Title A Supervised Graph-cut Deformable Model for Brain MRI Segmentation. Deformation models: tracking, animation and applications Type Book Chapter
  Year 2012 Publication Computational Vision and Biomechanics Abbreviated Journal  
  Volume Issue Pages  
  Keywords (up)  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Springer Netherlands Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-94-007-5445-4 Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ ISH2012b Serial 2066  
Permanent link to this record
 

 
Author Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga edit   pdf
doi  isbn
openurl 
  Title Coloresia: An Interactive Colour Perception Device for the Visually Impaired Type Book Chapter
  Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal  
  Volume 48 Issue Pages 47-66  
  Keywords (up)  
  Abstract A significative percentage of the human population suffer from impairments in their capacity to distinguish or even see colours. For them, everyday tasks like navigating through a train or metro network map becomes demanding. We present a novel technique for extracting colour information from everyday natural stimuli and presenting it to visually impaired users as pleasant, non-invasive sound. This technique was implemented inside a Personal Digital Assistant (PDA) portable device. In this implementation, colour information is extracted from the input image and categorised according to how human observers segment the colour space. This information is subsequently converted into sound and sent to the user via speakers or headphones. In the original implementation, it is possible for the user to send its feedback to reconfigure the system, however several features such as these were not implemented because the current technology is limited.We are confident that the full implementation will be possible in the near future as PDA technology improves.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium  
  Area Expedition Conference  
  Notes CIC; 600.052; 605.203 Approved no  
  Call Number Admin @ si @ GBP2013 Serial 2266  
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