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Author |
David Roche |
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Title  |
A Statistical Framework for Terminating Evolutionary Algorithms at their Steady State |
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Book Whole |
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2015 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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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. |
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July 2015 |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Debora Gil;Jesus Giraldo |
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IAM; 600.075 |
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no |
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Admin @ si @ Roc2015 |
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2686 |
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Author |
Hamdi Dibeklioglu; Albert Ali Salah; Theo Gevers |
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Title |
A Statistical Method for 2D Facial Landmarking |
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Journal Article |
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Year |
2012 |
Publication |
IEEE Transactions on Image Processing |
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TIP |
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21 |
Issue |
2 |
Pages |
844-858 |
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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). |
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1057-7149 |
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ALTRES;ISE |
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Admin @ si @ DSG 2012 |
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1853 |
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Author |
Mikhail Mozerov; V. Kober; I.A. Ovseyevich |
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Title |
A Stereo Matching Algorithm with Global Smoothness Criterion |
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Miscellaneous |
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2006 |
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Topical Meeting on Optoinformatics / Information Photonics, 133–135 |
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Saint-Petersburg (Russia) |
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ISE |
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ISE @ ise @ MKO2006 |
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675 |
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Author |
Josep Llados; Gemma Sanchez; Enric Marti |
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Title |
A string based method to recognize symbols and structural textures in architectural plans |
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Book Chapter |
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Year |
1998 |
Publication |
Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers |
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LNCS |
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1389 |
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1998 |
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91-103 |
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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. |
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Springer Link |
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DAG; IAM |
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IAM @ iam @ SLE1998 |
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1573 |
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Author |
Gemma Sanchez; Josep Llados; Enric Marti |
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Title |
A string-based method to recognize symbols and structural textures in architectural plans |
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Conference Article |
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1997 |
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2nd IAPR Workshop on Graphics Recognition |
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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. |
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Nancy, France |
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DAG; IAM |
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IAM @ iam @ SLE1997 |
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1498 |
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Author |
Josep Llados; Gemma Sanchez; Enric Marti |
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Title |
A String-Based Method to Recognize Symbols and Structural Textures in Architectural Plans. |
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Miscellaneous |
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1997 |
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Second IAPR Workshop on Graphics Recognition, pp. 287–294. |
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DAG @ dag @ LSM1997 |
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44 |
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Author |
David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados |
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Title |
A Study of Bag-of-Visual-Words Representations for Handwritten Keyword Spotting |
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Journal Article |
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2015 |
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International Journal on Document Analysis and Recognition |
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IJDAR |
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18 |
Issue |
3 |
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223-234 |
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Bag-of-Visual-Words; Keyword spotting; Handwritten documents; Performance evaluation |
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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. |
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Springer Berlin Heidelberg |
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1433-2833 |
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DAG; ADAS; 600.055; 600.061; 601.223; 600.077; 600.097 |
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Admin @ si @ ART2015 |
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2679 |
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Author |
Yasuko Sugito; Trevor Canham; Javier Vazquez; Marcelo Bertalmio |
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A Study of Objective Quality Metrics for HLG-Based HDR/WCG Image Coding |
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2021 |
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SMPTE Motion Imaging Journal |
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SMPTE |
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130 |
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4 |
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53 - 65 |
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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. |
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CIC |
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SCV2021 |
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3671 |
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Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Oscar Vilarroya; Petia Radeva |
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A Supervised Graph-cut Deformable Model for Brain MRI Segmentation. Deformation models: tracking, animation and applications |
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2012 |
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Computational Vision and Biomechanics |
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Springer Netherlands |
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978-94-007-5445-4 |
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MILAB;HuPBA |
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Admin @ si @ ISH2012b |
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2066 |
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A. Pujol; Juan J. Villanueva |
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A supervised Modification of the Hausdorff distance for visual shape classification |
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2002 |
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International Journal of Pattern Recognition and Artificial Intelligence |
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16 |
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3 |
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349-359 |
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(IF: 0.359) |
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PuV2002 |
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273 |
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Bogdan Raducanu; Fadi Dornaika |
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A Supervised Non-linear Dimensionality Reduction Approach for Manifold Learning |
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2012 |
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Pattern Recognition |
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PR |
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45 |
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6 |
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2432-2444 |
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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. |
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Elsevier |
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OR; MV |
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Admin @ si @ RaD2012a |
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1884 |
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Xavier Otazu; Maria Vanrell |
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A surround-induction function to unify assimilation and contrast in a computational model of color apearance |
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2005 |
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Perception supplement, ECVP05 Abstracts, 34: 215 |
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568 |
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David Castells; Vinh Ngo; Juan Borrego-Carazo; Marc Codina; Carles Sanchez; Debora Gil; Jordi Carrabina |
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A Survey of FPGA-Based Vision Systems for Autonomous Cars |
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2022 |
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IEEE Access |
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ACESS |
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10 |
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132525-132563 |
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Autonomous automobile; Computer vision; field programmable gate arrays; reconfigurable architectures |
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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. |
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16 December 2022 |
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IEEE |
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IAM; 600.166 |
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Admin @ si @ CNB2022 |
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3760 |
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Maryam Asadi-Aghbolaghi; Albert Clapes; Marco Bellantonio; Hugo Jair Escalante; Victor Ponce; Xavier Baro; Isabelle Guyon; Shohreh Kasaei; Sergio Escalera |
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A survey on deep learning based approaches for action and gesture recognition in image sequences |
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2017 |
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12th IEEE International Conference on Automatic Face and Gesture Recognition |
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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. |
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Washington; USA; May 2017 |
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HUPBA; no proj |
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no |
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Admin @ si @ ACB2017b |
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2982 |
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Xavier Perez Sala; Sergio Escalera; Cecilio Angulo; Jordi Gonzalez |
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A survey on model based approaches for 2D and 3D visual human pose recovery |
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Journal Article |
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2014 |
Publication |
Sensors |
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SENS |
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14 |
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3 |
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4189-4210 |
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human pose recovery; human body modelling; behavior analysis; computer vision |
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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. |
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HuPBA; ISE; 600.046; 600.063; 600.078;MILAB |
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Admin @ si @ PEA2014 |
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2443 |
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