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Ernest Valveny; Enric Marti |
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Hand-drawn symbol recognition in graphic documents using deformable template matching and a Bayesian framework |
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2000 |
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Proc. 15th Int Pattern Recognition Conf |
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2 |
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239-242 |
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Hand-drawn symbols can take many different and distorted shapes from their ideal representation. Then, very flexible methods are needed to be able to handle unconstrained drawings. We propose here to extend our previous work in hand-drawn symbol recognition based on a Bayesian framework and deformable template matching. This approach gets flexibility enough to fit distorted shapes in the drawing while keeping fidelity to the ideal shape of the symbol. In this work, we define the similarity measure between an image and a symbol based on the distance from every pixel in the image to the lines in the symbol. Matching is carried out using an implementation of the EM algorithm. Thus, we can improve recognition rates and computation time with respect to our previous formulation based on a simulated annealing algorithm. |
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0-7695-0750-6 |
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IAM @ iam @ VAM2000 |
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1656 |
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Author |
Ernest Valveny; Enric Marti |
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Title |
Application of deformable template matching to symbol recognition in hand-written architectural draw |
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1999 |
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Proceedings of the Fifth International Conference on |
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We propose to use deformable template matching as a new approach to recognize characters and lineal symbols in hand-written line drawings, instead of traditional methods based on vectorization and feature extraction. Bayesian formulation of the deformable template matching allows combining fidelity to the ideal shape of the symbol with maximum flexibility to get the best fit to the input image. Lineal nature of symbols can be exploited to define a suitable representation of models and the set of deformations to be applied to them. Matching, however, is done over the original binary image to avoid losing relevant features during vectorization. We have applied this method to hand-written architectural drawings and experimental results demonstrate that symbols with high distortions from ideal shape can be accurately identified. |
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Bangalore (India) |
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DAG;IAM; |
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IAM @ iam @ VAM1999a |
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1657 |
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Author |
Ernest Valveny; Enric Marti |
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Recognition of lineal symbols in hand-written drawings using deformable template matching |
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1999 |
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Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Análisis de Imágenes |
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DAG;IAM; |
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IAM @ iam @ VAM1999 |
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1658 |
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Ernest Valveny; Enric Marti |
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Dimensions analysis in hand-drawn architectural drawings |
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1997 |
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(SNRFAI’97) 7th Spanish National Symposium on Pattern Recognition and Image Analysis |
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90-91 |
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CVC-UAB |
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DAG;IAM; |
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IAM @ iam @ VAM1997 |
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1659 |
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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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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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David Roche; Debora Gil; Jesus Giraldo |
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An inference model for analyzing termination conditions of Evolutionary Algorithms |
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2011 |
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14th Congrès Català en Intel·ligencia Artificial |
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216-225 |
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Evolutionary Computation Convergence, Termination Conditions, Statistical Inference |
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In real-world problems, it is mandatory to design a termination condition for Evolutionary Algorithms (EAs) ensuring stabilization close to the unknown optimum. Distribution-based quantities are good candidates as far as suitable parameters are used. A main limitation for application to real-world problems is that such parameters strongly depend on the topology of the objective function, as well as, the EA paradigm used.
We claim that the termination problem would be fully solved if we had a model measuring to what extent a distribution-based quantity asymptotically behaves like the solution accuracy. We present a regression-prediction model that relates any two given quantities and reports if they can be statistically swapped as termination conditions. Our framework is applied to two issues. First, exploring if the parameters involved in the computation of distribution-based quantities influence their asymptotic behavior. Second, to what extent existing distribution-based quantities can be asymptotically exchanged for the accuracy of the EA solution. |
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Lleida, Catalonia (Spain) |
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Associació Catalana Intel·ligència Artificial |
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978-1-60750-841-0 |
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CCIA |
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IAM @ iam @ RGG2011a |
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1677 |
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David Roche; Debora Gil; Jesus Giraldo |
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Using statistical inference for designing termination conditions ensuring convergence of Evolutionary Algorithms |
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2011 |
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11th European Conference on Artificial Life |
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A main challenge in Evolutionary Algorithms (EAs) is determining a termination condition ensuring stabilization close to the optimum in real-world applications. Although for known test functions distribution-based quantities are good candidates (as far as suitable parameters are used), in real-world problems an open question still remains unsolved. How can we estimate an upper-bound for the termination condition value ensuring a given accuracy for the (unknown) EA solution?
We claim that the termination problem would be fully solved if we defined a quantity (depending only on the EA output) behaving like the solution accuracy. The open question would be, then, satisfactorily answered if we had a model relating both quantities, since accuracy could be predicted from the alternative quantity. We present a statistical inference framework addressing two topics: checking the correlation between the two quantities and defining a regression model for predicting (at a given confidence level) accuracy values from the EA output. |
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Paris, France |
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ECAL |
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IAM; |
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IAM @ iam @ RGG2011b |
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1678 |
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Ferran Poveda; Debora Gil ;Albert Andaluz ;Enric Marti |
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Multiscale Tractography for Representing Heart Muscular Architecture |
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2011 |
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In MICCAI 2011 Workshop on Computational Diffusion MRI |
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Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. Although the muscular architecture of the heart has been debated by countless researchers, the controversy is still alive. Diffusion Tensor MRI, DT-MRI, is a unique imaging technique for computational validation of the muscular structure of the heart. By the complex arrangement of myocites, existing techniques can not provide comprehensive descriptions of the global muscular architecture. In this paper we introduce a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and indicate a global helical organization |
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English |
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english |
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CDRMI |
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IAM |
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IAM @ iam @ PGA2011 |
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1681 |
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Andrew Nolan; Daniel Serrano; Aura Hernandez-Sabate; Daniel Ponsa; Antonio Lopez |
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Obstacle mapping module for quadrotors on outdoor Search and Rescue operations |
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2013 |
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International Micro Air Vehicle Conference and Flight Competition |
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UAV |
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Obstacle avoidance remains a challenging task for Micro Aerial Vehicles (MAV), due to their limited payload capacity to carry advanced sensors. Unlike larger vehicles, MAV can only carry light weight sensors, for instance a camera, which is our main assumption in this work. We explore passive monocular depth estimation and propose a novel method Position Aided Depth Estimation
(PADE). We analyse PADE performance and compare it against the extensively used Time To Collision (TTC). We evaluate the accuracy, robustness to noise and speed of three Optical Flow (OF) techniques, combined with both depth estimation methods. Our results show PADE is more accurate than TTC at depths between 0-12 meters and is less sensitive to noise. Our findings highlight the potential application of PADE for MAV to perform safe autonomous navigation in
unknown and unstructured environments. |
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Toulouse; France; September 2013 |
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IMAV |
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ADAS; 600.054; 600.057;IAM |
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Admin @ si @ NSH2013 |
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Debora Gil; Agnes Borras; Manuel Ballester; Francesc Carreras; Ruth Aris; Manuel Vazquez; Enric Marti; Ferran Poveda |
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MIOCARDIA: Integrating cardiac function and muscular architecture for a better diagnosis |
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2011 |
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14th International Symposium on Applied Sciences in Biomedical and Communication Technologies |
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Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. The MIOCARDIA project is a multidisciplinary project in cooperation with l'Hospital de la Santa Creu i de Sant Pau, Clinica la Creu Blanca and Barcelona Supercomputing Center. The ultimate goal of this project is defining a computational model of the myocardium. The model takes into account the deep interrelation between the anatomy and the mechanics of the heart. The paper explains the workflow of the MIOCARDIA project. It also introduces a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and provides evidences of a global helical organization. |
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Barcelona; Spain |
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Association for Computing Machinery |
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Barcelona, Spain |
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Association for Computing Machinery |
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english |
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english |
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978-1-4503-0913-4 |
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ISABEL |
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IAM |
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IAM @ iam @ GGB2011 |
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1691 |
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