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Author David Roche
Title (up) A Statistical Framework for Terminating Evolutionary Algorithms at their Steady State Type Book Whole
Year 2015 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract As any iterative technique, it is a necessary condition a stop criterion for terminating Evolutionary Algorithms (EA). In the case of optimization methods, the algorithm should stop at the time it has reached a steady state so it can not improve results anymore. Assessing the reliability of termination conditions for EAs is of prime importance. A wrong or weak stop criterion can negatively a ect both the computational e ort and the nal result.
In this Thesis, we introduce a statistical framework for assessing whether a termination condition is able to stop EA at its steady state. In one hand a numeric approximation to steady states to detect the point in which EA population has lost its diversity has been presented for EA termination. This approximation has been applied to di erent EA paradigms based on diversity and a selection of functions covering the properties most relevant for EA convergence. Experiments show that our condition works regardless of the search space dimension and function landscape and Di erential Evolution (DE) arises as the best paradigm. On the other hand, we use a regression model in order to determine the requirements ensuring that a measure derived from EA evolving population is related to the distance to the optimum in xspace.
Our theoretical framework is analyzed across several benchmark test functions
and two standard termination criteria based on function improvement in f-space and EA population x-space distribution for the DE paradigm. Results validate our statistical framework as a powerful tool for determining the capability of a measure for terminating EA and select the x-space distribution as the best-suited for accurately stopping DE in real-world applications.
Address July 2015
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Debora Gil;Jesus Giraldo
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM; 600.075 Approved no
Call Number Admin @ si @ Roc2015 Serial 2686
Permanent link to this record
 
 
Author Hamdi Dibeklioglu; Albert Ali Salah; Theo Gevers
Title (up) A Statistical Method for 2D Facial Landmarking Type Journal Article
Year 2012 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 21 Issue 2 Pages 844-858
Keywords
Abstract IF = 3.32
Many facial-analysis approaches rely on robust and accurate automatic facial landmarking to correctly function. In this paper, we describe a statistical method for automatic facial-landmark localization. Our landmarking relies on a parsimonious mixture model of Gabor wavelet features, computed in coarse-to-fine fashion and complemented with a shape prior. We assess the accuracy and the robustness of the proposed approach in extensive cross-database conditions conducted on four face data sets (Face Recognition Grand Challenge, Cohn-Kanade, Bosphorus, and BioID). Our method has 99.33% accuracy on the Bosphorus database and 97.62% accuracy on the BioID database on the average, which improves the state of the art. We show that the method is not significantly affected by low-resolution images, small rotations, facial expressions, and natural occlusions such as beard and mustache. We further test the goodness of the landmarks in a facial expression recognition application and report landmarking-induced improvement over baseline on two separate databases for video-based expression recognition (Cohn-Kanade and BU-4DFE).
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 1057-7149 ISBN Medium
Area Expedition Conference
Notes ALTRES;ISE Approved no
Call Number Admin @ si @ DSG 2012 Serial 1853
Permanent link to this record
 
 
Author Mikhail Mozerov; V. Kober; I.A. Ovseyevich
Title (up) A Stereo Matching Algorithm with Global Smoothness Criterion Type Miscellaneous
Year 2006 Publication Topical Meeting on Optoinformatics / Information Photonics, 133–135 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Saint-Petersburg (Russia)
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 ISE Approved no
Call Number ISE @ ise @ MKO2006 Serial 675
Permanent link to this record
 
 
Author Josep Llados; Gemma Sanchez; Enric Marti
Title (up) A string based method to recognize symbols and structural textures in architectural plans Type Book Chapter
Year 1998 Publication Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers Abbreviated Journal LNCS
Volume 1389 Issue 1998 Pages 91-103
Keywords
Abstract This paper deals with the recognition of symbols and structural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clustering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the similarity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion.
Address
Corporate Author Thesis
Publisher Springer Link Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title LNCS Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG; IAM Approved no
Call Number IAM @ iam @ SLE1998 Serial 1573
Permanent link to this record
 
 
Author Gemma Sanchez; Josep Llados; Enric Marti
Title (up) A string-based method to recognize symbols and structural textures in architectural plans Type Conference Article
Year 1997 Publication 2nd IAPR Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper deals with the recognition of symbols and struc- tural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clus- tering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the simila- rity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion.
Address Nancy, France
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 DAG; IAM Approved no
Call Number IAM @ iam @ SLE1997 Serial 1498
Permanent link to this record
 
 
Author Josep Llados; Gemma Sanchez; Enric Marti
Title (up) A String-Based Method to Recognize Symbols and Structural Textures in Architectural Plans. Type Miscellaneous
Year 1997 Publication Second IAPR Workshop on Graphics Recognition, pp. 287–294. 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 DAG Approved no
Call Number DAG @ dag @ LSM1997 Serial 44
Permanent link to this record
 
 
Author David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados
Title (up) A Study of Bag-of-Visual-Words Representations for Handwritten Keyword Spotting Type Journal Article
Year 2015 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 18 Issue 3 Pages 223-234
Keywords Bag-of-Visual-Words; Keyword spotting; Handwritten documents; Performance evaluation
Abstract The Bag-of-Visual-Words (BoVW) framework has gained popularity among the document image analysis community, specifically as a representation of handwritten words for recognition or spotting purposes. Although in the computer vision field the BoVW method has been greatly improved, most of the approaches in the document image analysis domain still rely on the basic implementation of the BoVW method disregarding such latest refinements. In this paper, we present a review of those improvements and its application to the keyword spotting task. We thoroughly evaluate their impact against a baseline system in the well-known George Washington dataset and compare the obtained results against nine state-of-the-art keyword spotting methods. In addition, we also compare both the baseline and improved systems with the methods presented at the Handwritten Keyword Spotting Competition 2014.
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 1433-2833 ISBN Medium
Area Expedition Conference
Notes DAG; ADAS; 600.055; 600.061; 601.223; 600.077; 600.097 Approved no
Call Number Admin @ si @ ART2015 Serial 2679
Permanent link to this record
 
 
Author Yasuko Sugito; Trevor Canham; Javier Vazquez; Marcelo Bertalmio
Title (up) A Study of Objective Quality Metrics for HLG-Based HDR/WCG Image Coding Type Journal
Year 2021 Publication SMPTE Motion Imaging Journal Abbreviated Journal SMPTE
Volume 130 Issue 4 Pages 53 - 65
Keywords
Abstract In this work, we study the suitability of high dynamic range, wide color gamut (HDR/WCG) objective quality metrics to assess the perceived deterioration of compressed images encoded using the hybrid log-gamma (HLG) method, which is the standard for HDR television. Several image quality metrics have been developed to deal specifically with HDR content, although in previous work we showed that the best results (i.e., better matches to the opinion of human expert observers) are obtained by an HDR metric that consists simply in applying a given standard dynamic range metric, called visual information fidelity (VIF), directly to HLG-encoded images. However, all these HDR metrics ignore the chroma components for their calculations, that is, they consider only the luminance channel. For this reason, in the current work, we conduct subjective evaluation experiments in a professional setting using compressed HDR/WCG images encoded with HLG and analyze the ability of the best HDR metric to detect perceivable distortions in the chroma components, as well as the suitability of popular color metrics (including ΔITPR , which supports parameters for HLG) to correlate with the opinion scores. Our first contribution is to show that there is a need to consider the chroma components in HDR metrics, as there are color distortions that subjects perceive but that the best HDR metric fails to detect. Our second contribution is the surprising result that VIF, which utilizes only the luminance channel, correlates much better with the subjective evaluation scores than the metrics investigated that do consider the color components.
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 CIC Approved no
Call Number SCV2021 Serial 3671
Permanent link to this record
 
 
Author Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Oscar Vilarroya; Petia Radeva
Title (up) 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
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 A. Pujol; Juan J. Villanueva
Title (up) A supervised Modification of the Hausdorff distance for visual shape classification Type Journal
Year 2002 Publication International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal
Volume 16 Issue 3 Pages 349-359
Keywords
Abstract (IF: 0.359)
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 ISE Approved no
Call Number PuV2002 Serial 273
Permanent link to this record
 
 
Author Bogdan Raducanu; Fadi Dornaika
Title (up) A Supervised Non-linear Dimensionality Reduction Approach for Manifold Learning Type Journal Article
Year 2012 Publication Pattern Recognition Abbreviated Journal PR
Volume 45 Issue 6 Pages 2432-2444
Keywords
Abstract IF= 2.61
IF=2.61 (2010)
In this paper we introduce a novel supervised manifold learning technique called Supervised Laplacian Eigenmaps (S-LE), which makes use of class label information to guide the procedure of non-linear dimensionality reduction by adopting the large margin concept. The graph Laplacian is split into two components: within-class graph and between-class graph to better characterize the discriminant property of the data. Our approach has two important characteristics: (i) it adaptively estimates the local neighborhood surrounding each sample based on data density and similarity and (ii) the objective function simultaneously maximizes the local margin between heterogeneous samples and pushes the homogeneous samples closer to each other.

Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques, demonstrating its superiority. 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 variations in their appearance (such as hand or body pose, for instance.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0031-3203 ISBN Medium
Area Expedition Conference
Notes OR; MV Approved no
Call Number Admin @ si @ RaD2012a Serial 1884
Permanent link to this record
 
 
Author Xavier Otazu; Maria Vanrell
Title (up) A surround-induction function to unify assimilation and contrast in a computational model of color apearance Type Miscellaneous
Year 2005 Publication Perception supplement, ECVP05 Abstracts, 34: 215 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 CIC Approved no
Call Number CAT @ cat @ OtV2005a Serial 568
Permanent link to this record
 
 
Author David Castells; Vinh Ngo; Juan Borrego-Carazo; Marc Codina; Carles Sanchez; Debora Gil; Jordi Carrabina
Title (up) A Survey of FPGA-Based Vision Systems for Autonomous Cars Type Journal Article
Year 2022 Publication IEEE Access Abbreviated Journal ACESS
Volume 10 Issue Pages 132525-132563
Keywords Autonomous automobile; Computer vision; field programmable gate arrays; reconfigurable architectures
Abstract On the road to making self-driving cars a reality, academic and industrial researchers are working hard to continue to increase safety while meeting technical and regulatory constraints Understanding the surrounding environment is a fundamental task in self-driving cars. It requires combining complex computer vision algorithms. Although state-of-the-art algorithms achieve good accuracy, their implementations often require powerful computing platforms with high power consumption. In some cases, the processing speed does not meet real-time constraints. FPGA platforms are often used to implement a category of latency-critical algorithms that demand maximum performance and energy efficiency. Since self-driving car computer vision functions fall into this category, one could expect to see a wide adoption of FPGAs in autonomous cars. In this paper, we survey the computer vision FPGA-based works from the literature targeting automotive applications over the last decade. Based on the survey, we identify the strengths and weaknesses of FPGAs in this domain and future research opportunities and challenges.
Address 16 December 2022
Corporate Author Thesis
Publisher IEEE 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 IAM; 600.166 Approved no
Call Number Admin @ si @ CNB2022 Serial 3760
Permanent link to this record
 
 
Author Maryam Asadi-Aghbolaghi; Albert Clapes; Marco Bellantonio; Hugo Jair Escalante; Victor Ponce; Xavier Baro; Isabelle Guyon; Shohreh Kasaei; Sergio Escalera
Title (up) A survey on deep learning based approaches for action and gesture recognition in image sequences Type Conference Article
Year 2017 Publication 12th IEEE International Conference on Automatic Face and Gesture Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract The interest in action and gesture recognition has grown considerably in the last years. In this paper, we present a survey on current deep learning methodologies for action and gesture recognition in image sequences. We introduce a taxonomy that summarizes important aspects of deep learning
for approaching both tasks. We review the details of the proposed architectures, fusion strategies, main datasets, and competitions.
We summarize and discuss the main works proposed so far with particular interest on how they treat the temporal dimension of data, discussing their main features and identify opportunities and challenges for future research.
Address Washington; USA; May 2017
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 FG
Notes HUPBA; no proj Approved no
Call Number Admin @ si @ ACB2017b Serial 2982
Permanent link to this record
 
 
Author Xavier Perez Sala; Sergio Escalera; Cecilio Angulo; Jordi Gonzalez
Title (up) A survey on model based approaches for 2D and 3D visual human pose recovery Type Journal Article
Year 2014 Publication Sensors Abbreviated Journal SENS
Volume 14 Issue 3 Pages 4189-4210
Keywords human pose recovery; human body modelling; behavior analysis; computer vision
Abstract Human Pose Recovery has been studied in the field of Computer Vision for the last 40 years. Several approaches have been reported, and significant improvements have been obtained in both data representation and model design. However, the problem of Human Pose Recovery in uncontrolled environments is far from being solved. In this paper, we define a general taxonomy to group model based approaches for Human Pose Recovery, which is composed of five main modules: appearance, viewpoint, spatial relations, temporal consistence, and behavior. Subsequently, a methodological comparison is performed following the proposed taxonomy, evaluating current SoA approaches in the aforementioned five group categories. As a result of this comparison, we discuss the main advantages and drawbacks of the reviewed literature.
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 HuPBA; ISE; 600.046; 600.063; 600.078;MILAB Approved no
Call Number Admin @ si @ PEA2014 Serial 2443
Permanent link to this record