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Author Alicia Fornes; Sergio Escalera; Josep Llados; Gemma Sanchez; Joan Mas edit  openurl
  Title (down) Hand Drawn Symbol Recognition by Blurred Shape Model Descriptor and a Multiclass Classifier Type Book Chapter
  Year 2008 Publication Graphics Recognition: Recent Advances and New Opportunities Abbreviated Journal  
  Volume 5046 Issue Pages 30–40  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor W. Liu, J. Llados, J.M. Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; HUPBA; MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ FEL2008 Serial 989  
Permanent link to this record
 

 
Author Ole Vilhelm-Larsen; Petia Radeva; Enric Marti edit   pdf
doi  openurl
  Title (down) Guidelines for choosing optimal parameters of elasticity for snakes Type Book Chapter
  Year 1995 Publication Computer Analysis Of Images And Patterns Abbreviated Journal LNCS  
  Volume 970 Issue Pages 106-113  
  Keywords  
  Abstract This paper proposes a guidance in the process of choosing and using the parameters of elasticity of a snake in order to obtain a precise segmentation. A new two step procedure is defined based on upper and lower bounds on the parameters. Formulas, by which these bounds can be calculated for real images where parts of the contour may be missing, are presented. Experiments on segmentation of bone structures in X-ray images have verified the usefulness of the new procedure.  
  Address  
  Corporate Author Thesis  
  Publisher 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 ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;IAM Approved no  
  Call Number IAM @ iam @ LRM1995b Serial 1558  
Permanent link to this record
 

 
Author Josep Llados; Marçal Rusiñol edit  doi
isbn  openurl
  Title (down) 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.  
  Address  
  Corporate Author Thesis  
  Publisher Springer London Place of Publication Editor D. Doermann; K. Tombre  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  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 Ivan Huerta; Ariel Amato; Jordi Gonzalez; Juan J. Villanueva edit  openurl
  Title (down) Fusing Edge Cues to Handle Colour Problems in Image Segmentation Type Book Chapter
  Year 2008 Publication Articulated Motion and Deformable Objects, 5th International Conference Abbreviated Journal  
  Volume 5098 Issue Pages 279–288  
  Keywords  
  Abstract  
  Address Port d'Andratx (Mallorca)  
  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 AMDO  
  Notes ISE Approved no  
  Call Number ISE @ ise @ HAG2008 Serial 973  
Permanent link to this record
 

 
Author Antonio Lopez; Jiaolong Xu; Jose Luis Gomez; David Vazquez; German Ros edit   pdf
openurl 
  Title (down) From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example Type Book Chapter
  Year 2017 Publication Domain Adaptation in Computer Vision Applications Abbreviated Journal  
  Volume Issue 13 Pages 243-258  
  Keywords Domain Adaptation  
  Abstract Supervised learning tends to produce more accurate classifiers than unsupervised learning in general. This implies that training data is preferred with annotations. When addressing visual perception challenges, such as localizing certain object classes within an image, the learning of the involved classifiers turns out to be a practical bottleneck. The reason is that, at least, we have to frame object examples with bounding boxes in thousands of images. A priori, the more complex the model is regarding its number of parameters, the more annotated examples are required. This annotation task is performed by human oracles, which ends up in inaccuracies and errors in the annotations (aka ground truth) since the task is inherently very cumbersome and sometimes ambiguous. As an alternative we have pioneered the use of virtual worlds for collecting such annotations automatically and with high precision. However, since the models learned with virtual data must operate in the real world, we still need to perform domain adaptation (DA). In this chapter we revisit the DA of a deformable part-based model (DPM) as an exemplifying case of virtual- to-real-world DA. As a use case, we address the challenge of vehicle detection for driver assistance, using different publicly available virtual-world data. While doing so, we investigate questions such as: how does the domain gap behave due to virtual-vs-real data with respect to dominant object appearance per domain, as well as the role of photo-realism in the virtual world.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor Gabriela Csurka  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS; 600.085; 601.223; 600.076; 600.118 Approved no  
  Call Number ADAS @ adas @ LXG2017 Serial 2872  
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Author Svebor Karaman; Giuseppe Lisanti; Andrew Bagdanov; Alberto del Bimbo edit  doi
isbn  openurl
  Title (down) From re-identification to identity inference: Labeling consistency by local similarity constraints Type Book Chapter
  Year 2014 Publication Person Re-Identification Abbreviated Journal  
  Volume 2 Issue Pages 287-307  
  Keywords re-identification; Identity inference; Conditional random fields; Video surveillance  
  Abstract In this chapter, we introduce the problem of identity inference as a generalization of person re-identification. It is most appropriate to distinguish identity inference from re-identification in situations where a large number of observations must be identified without knowing a priori that groups of test images represent the same individual. The standard single- and multishot person re-identification common in the literature are special cases of our formulation. We present an approach to solving identity inference by modeling it as a labeling problem in a Conditional Random Field (CRF). The CRF model ensures that the final labeling gives similar labels to detections that are similar in feature space. Experimental results are given on the ETHZ, i-LIDS and CAVIAR datasets. Our approach yields state-of-the-art performance for multishot re-identification, and our results on the more general identity inference problem demonstrate that we are able to infer the identity of very many examples even with very few labeled images in the gallery.  
  Address  
  Corporate Author Thesis  
  Publisher Springer London Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2191-6586 ISBN 978-1-4471-6295-7 Medium  
  Area Expedition Conference  
  Notes LAMP; 600.079 Approved no  
  Call Number Admin @ si @KLB2014b Serial 2521  
Permanent link to this record
 

 
Author Marçal Rusiñol; Josep Llados edit  openurl
  Title (down) Flowchart Recognition in Patent Information Retrieval Type Book Chapter
  Year 2017 Publication Current Challenges in Patent Information Retrieval Abbreviated Journal  
  Volume 37 Issue Pages 351-368  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor M. Lupu; K. Mayer; N. Kando; A.J. Trippe  
  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; 600.097; 600.121 Approved no  
  Call Number Admin @ si @ RuL2017 Serial 2896  
Permanent link to this record
 

 
Author Xavier Baro; Jordi Vitria edit  openurl
  Title (down) Feature Selection with Non-Parametric Mutual Information for Adaboost Learning Type Book Chapter
  Year 2005 Publication Frontiers in Artificial Intelligence and Applications / Artificial intelligence Research and Development, 131:131–138, Eds: B. Lopez, J. Melendez, P. Radeva, J. Vitria, IOS Press, ISBN: 1–58603–560–6 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher 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 OR;HuPBA;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ BaV2005b Serial 583  
Permanent link to this record
 

 
Author Fadi Dornaika; Bogdan Raducanu edit  openurl
  Title (down) Facial Expression Recognition for HCI Applications Type Book Chapter
  Year 2008 Publication Encyclopedia of Artificial Intelligence Abbreviated Journal  
  Volume II Issue Pages 625–631  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher IGI–Global Publisher Place of Publication Editor Rabuñal  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ DoR2008c Serial 1034  
Permanent link to this record
 

 
Author Fadi Dornaika; Bogdan Raducanu; Alireza Bosaghzadeh edit  openurl
  Title (down) Facial expression recognition based on multi observations with application to social robotics Type Book Chapter
  Year 2015 Publication Emotional and Facial Expressions: Recognition, Developmental Differences and Social Importance Abbreviated Journal  
  Volume Issue Pages 153-166  
  Keywords  
  Abstract Human-robot interaction is a hot topic nowadays in the social robotics
community. One crucial aspect is represented by the affective communication
which comes encoded through the facial expressions. In this chapter, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, viewand texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial
expression.
 
  Address  
  Corporate Author Thesis  
  Publisher Nova Science publishers Place of Publication Editor Bruce Flores  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes LAMP; Approved no  
  Call Number Admin @ si @ DRB2015 Serial 2720  
Permanent link to this record
 

 
Author Quan-sen Sun; Pheng-ann Heng; Zhong Jin; De-shen Xia edit  openurl
  Title (down) Face recognition based on generalized canonical correlation analysis Type Book Chapter
  Year 2005 Publication Advances in Intelligent Computing, Lecture Notes in Computer Science, 3645: 958–967 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Hefei (China)  
  Corporate Author Thesis  
  Publisher 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 Approved no  
  Call Number Admin @ si @ SHJ2005 Serial 625  
Permanent link to this record
 

 
Author Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li edit  url
openurl 
  Title (down) Face Presentation Attack Detection (PAD) Challenges Type Book Chapter
  Year 2023 Publication Advances in Face Presentation Attack Detection Abbreviated Journal  
  Volume Issue Pages 17–35  
  Keywords  
  Abstract In recent years, the security of face recognition systems has been increasingly threatened. Face Anti-spoofing (FAS) is essential to secure face recognition systems primarily from various attacks. In order to attract researchers and push forward the state of the art in Face Presentation Attack Detection (PAD), we organized three editions of Face Anti-spoofing Workshop and Competition at CVPR 2019, CVPR 2020, and ICCV 2021, which have attracted more than 800 teams from academia and industry, and greatly promoted the algorithms to overcome many challenging problems. In this chapter, we introduce the detailed competition process, including the challenge phases, timeline and evaluation metrics. Along with the workshop, we will introduce the corresponding dataset for each competition including data acquisition details, data processing, statistics, and evaluation protocol. Finally, we provide the available link to download the datasets used in the challenges.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title SLCV  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes HUPBA Approved no  
  Call Number Admin @ si @ WGE2023b Serial 3956  
Permanent link to this record
 

 
Author Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li edit  url
openurl 
  Title (down) Face Anti-spoofing Progress Driven by Academic Challenges Type Book Chapter
  Year 2023 Publication Advances in Face Presentation Attack Detection Abbreviated Journal  
  Volume Issue Pages 1–15  
  Keywords  
  Abstract With the ubiquity of facial authentication systems and the prevalence of security cameras around the world, the impact that facial presentation attack techniques may have is huge. However, research progress in this field has been slowed by a number of factors, including the lack of appropriate and realistic datasets, ethical and privacy issues that prevent the recording and distribution of facial images, the little attention that the community has given to potential ethnic biases among others. This chapter provides an overview of contributions derived from the organization of academic challenges in the context of face anti-spoofing detection. Specifically, we discuss the limitations of benchmarks and summarize our efforts in trying to boost research by the community via the participation in academic challenges  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title SLCV  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes HUPBA Approved no  
  Call Number Admin @ si @ WGE2023c Serial 3957  
Permanent link to this record
 

 
Author F.Guirado; Ana Ripoll; C.Roig; Aura Hernandez-Sabate; Emilio Luque edit   pdf
openurl 
  Title (down) Exploiting Throughput for Pipeline Execution in Streaming Image Processing Applications Type Book Chapter
  Year 2006 Publication Euro-Par 2006 Parallel Processing Abbreviated Journal LNCS  
  Volume 4128 Issue Pages 1095-1105  
  Keywords 12th International Euro–Par Conference  
  Abstract There is a large range of image processing applications that act on an input sequence of image frames that are continuously received. Throughput is a key performance measure to be optimized when execu- ting them. In this paper we propose a new task replication methodology for optimizing throughput for an image processing application in the field of medicine. The results show that by applying the proposed methodo- logy we are able to achieve the desired throughput in all cases, in such a way that the input frames can be processed at any given rate.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin Heidelberg Place of Publication Dresden, Germany (European Union) Editor UAB; W, E.N.; et al.  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes In Computer Science Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference Euro–Par  
  Notes IAM Approved no  
  Call Number IAM @ iam @ GRR2006a Serial 1542  
Permanent link to this record
 

 
Author Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez edit  openurl
  Title (down) 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  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier Science and Tech 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 ISE Approved no  
  Call Number ISE @ ise @ FBR2009 Serial 1212  
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