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Josefina Mauri; Eduard Fernandez-Nofrerias; B. Garcia del Blanco; E. Iraculis; J.A. Gomez-Hospital; J. Comin; M.A. Sanchez Corral; F. Jara; A. Cequier; E. Esplugas; Debora Gil; J. Saludes; Petia Radeva; Ricardo Toledo; Juan J.Villanueva |
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Moviment del vas en l anàlisi d imatges d ecografia intracoronària: un model matemàtic |
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2000 |
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Congrés de la Societat Catalana de Cardiologia. |
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IAM;RV;ISE;MILAB;ADAS |
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IAM @ iam @ MNG2000 |
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1621 |
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Josefina Mauri; Eduard Fernandez-Nofrerias; J. Comin; B. Garcia del Blanco; E. Iraculis; J.A. Gomez-Hospital; P. Valdovinos; F. Jara; A. Cequier; E. Esplugas; Oriol Pujol; Cristina Cañero; Debora Gil; Petia Radeva; Ricardo Toledo |
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Title |
Avaluació del Conjunt Stent/Artèria mitjançant ecografia intracoronària: lentorn informàtic |
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Conference Article |
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2000 |
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Congrés de la Societat Catalana de Cardiologia. |
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IAM;RV;MILAB;ADAS;HuPBA |
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IAM @ iam @ MNC2000 |
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1622 |
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Petia Radeva; Joan Serrat; Enric Marti |
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A snake for model-based segmentation |
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1995 |
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Proc. Conf. Fifth Int Computer Vision |
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816-821 |
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snakes; elastic matching; model-based segmenta tion |
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Despite the promising results of numerous applications, the hitherto proposed snake techniques share some common problems: snake attraction by spurious edge points, snake degeneration (shrinking and attening), convergence and stability of the deformation process, snake initialization and local determination of the parameters of elasticity. We argue here that these problems can be solved only when all the snake aspects are considered. The snakes proposed here implement a new potential eld and external force in order to provide a deformation convergence, attraction by both near and far edges as well as snake behaviour selective according to the edge orientation. Furthermore, we conclude that in the case of model-based seg mentation, the internal force should include structural information about the expected snake shape. Experiments using this kind of snakes for segmenting bones in complex hand radiographs show a signi cant improvement. |
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MILAB;ADAS;IAM |
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IAM @ iam @ RSM1995 |
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1634 |
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Oriol Rodriguez-Leon; Josefina Mauri; Eduard Fernandez-Nofrerias; M.Gomez; Antonio Tovar; L.Cano; C.Diego; Carme Julia; Vicente del Valle; Debora Gil; Petia Radeva |
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Title |
Ecografia Intracoronària: Segmentació Automàtica de area de la llum |
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Conference Article |
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2002 |
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XXXVIII Congreso Nacional de la Sociedad Española de Cardiología. |
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IAM;ADAS;MILAB |
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IAM @ iam @ RMF2002 |
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1638 |
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Joan Serrat; Enric Marti |
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Elastic matching using interpolation splines |
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1991 |
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IV Spanish Symposium of Pattern Recognition and image Analysis |
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ADAS;IAM; |
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IAM @ iam @ SMV1991 |
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1651 |
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Ernest Valveny; Ricardo Toledo; Ramon Baldrich; Enric Marti |
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Combining recognition-based in segmentation-based approaches for graphic symol recognition using deformable template matching |
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Conference Article |
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2002 |
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Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002 |
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502–507 |
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DAG;RV;CAT;IAM;CIC;ADAS |
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IAM @ iam @ VTB2002 |
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1660 |
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Author |
Muhammad Anwer Rao; David Vazquez; Antonio Lopez |
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Title |
Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
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Conference Article |
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2011 |
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14th International Conference on Computer Analysis of Images and Patterns |
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6855 |
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II |
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463-470 |
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Pedestrian Detection; Color |
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Abstract |
Camera-based person detection is of paramount interest due to its potential applications. The task is diffcult because the great variety of backgrounds (scenarios, illumination) in which persons are present, as well as their intra-class variability (pose, clothe, occlusion). In fact, the class person is one of the included in the popular PASCAL visual object classes (VOC) challenge. A breakthrough for this challenge, regarding person detection, is due to Felzenszwalb et al. These authors proposed a part-based detector that relies on histograms of oriented gradients (HOG) and latent support vector machines (LatSVM) to learn a model of the whole human body and its constitutive parts, as well as their relative position. Since the approach of Felzenszwalb et al. appeared new variants have been proposed, usually giving rise to more complex models. In this paper, we focus on an issue that has not attracted suficient interest up to now. In particular, we refer to the fact that HOG is usually computed from RGB color space, but other possibilities exist and deserve the corresponding investigation. In this paper we challenge RGB space with the opponent color space (OPP), which is inspired in the human vision system.We will compute the HOG on top of OPP, then we train and test the part-based human classifer by Felzenszwalb et al. using PASCAL VOC challenge protocols and person database. Our experiments demonstrate that OPP outperforms RGB. We also investigate possible differences among types of scenarios: indoor, urban and countryside. Interestingly, our experiments suggest that the beneficts of OPP with respect to RGB mainly come for indoor and countryside scenarios, those in which the human visual system was designed by evolution. |
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Seville, Spain |
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Springer |
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Berlin Heidelberg |
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P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
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English |
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english |
Original Title |
Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
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0302-9743 |
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978-3-642-23677-8 |
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CAIP |
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ADAS |
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ADAS @ adas @ RVL2011b |
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1665 |
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Author |
Muhammad Anwer Rao; David Vazquez; Antonio Lopez |
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Title |
Opponent Colors for Human Detection |
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Conference Article |
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2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
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6669 |
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363-370 |
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Pedestrian Detection; Color; Part Based Models |
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Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper. |
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Las Palmas de Gran Canaria. Spain |
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Springer |
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Berlin Heidelberg |
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J. Vitria; J.M. Sanches; M. Hernandez |
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English |
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English |
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Opponent Colors for Human Detection |
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Lecture Notes on Computer Science |
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LNCS |
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0302-9743 |
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978-3-642-21256-7 |
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IbPRIA |
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ADAS |
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ADAS @ adas @ RVL2011a |
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1666 |
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Author |
Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie |
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Title |
Inferring the Performance of Medical Imaging Algorithms |
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Conference Article |
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2011 |
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14th International Conference on Computer Analysis of Images and Patterns |
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6854 |
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520-528 |
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Validation, Statistical Inference, Medical Imaging Algorithms. |
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Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence. |
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Sevilla |
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Springer-Verlag Berlin Heidelberg |
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Berlin |
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Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch |
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L |
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CAIP |
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IAM; ADAS |
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IAM @ iam @ HGR2011 |
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1676 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth |
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2011 |
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IEEE International Conference on Computer Vision – Workshops |
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2042-2049 |
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IEEE International Conference on Computer Vision – Workshops |
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Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems. |
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IEEE |
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Barcelona (Spain) |
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English |
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English |
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ICCVW |
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IAM; ADAS |
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IAM @ iam @ MGH2011 |
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1682 |
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