Ernest Valveny, & Enric Marti. (1999). Recognition of lineal symbols in hand-written drawings using deformable template matching. In Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Análisis de Imágenes.
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Ernest Valveny, & Enric Marti. (1997). Dimensions analysis in hand-drawn architectural drawings. In VII National Simposium of Pattern Recognition and image Analysis, SNRFAI´97 (pp. 90–91). CVC-UAB.
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Ernest Valveny, Ricardo Toledo, Ramon Baldrich, & Enric Marti. (2002). Combining recognition-based in segmentation-based approaches for graphic symol recognition using deformable template matching. In Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002 (502–507).
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Sergio Vera. (2010). Finger joint modelling from hand X-ray images for assessing rheumatoid arthritis (Vol. 164). Master's thesis, , Bellaterra 01893, Barcelona, Spain.
Abstract: Rheumatoid arthritis is an autoimmune, systemic, inflammatory disorder that mainly af- fects bone joints. While there is no cure for this disease, continuous advances on palliative treatments require frequent verification of patient’s illness evolution. Such evolution is mea- sured through several available semi-quantitative methods that require evaluation of hand and foot X-ray images. Accurate assessment is a time consuming task that requires highly trained personnel. This hinders a generalized use in clinical practice for early diagnose and disease follow-up. In the context of the automatization of such evaluation methods we present a method for detection and characterization of finger joints in hand radiography images. Several measures for assessing the reduction of joint space width are proposed. We compare for the first time such measures to the Van der Heijde score, the gold standard method for rheumatoid arthritis assessment. The proposed method outperforms existing strategies with a detection rate above 95%. Our comparison to Van der Heijde index shows a promising correlation that encourages further research.
Keywords: Rheumatoid arthritis; joint detection; X-ray; Van der Heijde score
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Fernando Vilariño, Debora Gil, & Petia Radeva. (2004). A Novel FLDA Formulation for Numerical Stability Analysis. In P. R. and I. A. J. Vitrià (Ed.), Recent Advances in Artificial Intelligence Research and Development (Vol. 113, pp. 77–84). IOS Press.
Abstract: Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision.
Keywords: Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision
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Fernando Vilariño, & Enric Marti. (2008). New didactic techniques in the EHES applying mobile technologies.
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David Vazquez, & Enrique Cabello. (2007). Empleo de sistemas biométricos faciales aplicados al reconocimiento de personas en aeropuertos. Bachelor's thesis, , .
Abstract: El presente proyecto se desarrolló a lo largo del año 2005 y 2006, probando un prototipo de un sistema de verificación facial con imágenes extraídas de las cámaras de video-vigilancia del aeropuerto de Barajas. Se diseñaron varios experimentos, agrupados en dos clases. En el primer tipo, el sistema es entre- nado con imágenes obtenidas en condiciones de laboratorio y luego probado con imágenes extraídas de las cámaras de video-vigilancia del aeropuerto de Barajas. En el segundo caso, tanto las imágenes de entrenamiento como las de prueba corresponden a imágenes extraídas de Barajas.
Se ha desarrollado un sistema completo, que incluye adquisición y digitalización de las imágenes, localización y recorte de las caras en escena, verificación de sujetos y obtención de resultados. Los resultados muestran que, en general, un sistema de verificación facial basado en imágenes puede ser una valiosa ayuda a un operario que deba estar vigilando amplias zonas.
Keywords: Surveillance; Face detection; Face recognition
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Ferran Poveda, Debora Gil, Albert Andaluz, & Enric Marti. (2011). Multiscale Tractography for Representing Heart Muscular Architecture. In In MICCAI 2011 Workshop on Computational Diffusion MRI.
Abstract: 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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Patricia Marquez, Debora Gil, & Aura Hernandez-Sabate. (2011). A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth. In IEEE International Conference on Computer Vision – Workshops (pp. 2042–2049). Barcelona (Spain): IEEE.
Abstract: 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.
Keywords: IEEE International Conference on Computer Vision – Workshops
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Aura Hernandez-Sabate, & Debora Gil. (2012). The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries. In Yasuhiro Honda (Ed.), Intravascular Ultrasound (pp. 185–206). Intech.
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Lluis Pere de las Heras, Ahmed Sheraz, Marcus Liwicki, Ernest Valveny, & Gemma Sanchez. (2014). Statistical Segmentation and Structural Recognition for Floor Plan Interpretation. IJDAR - International Journal on Document Analysis and Recognition, 17(3), 221–237.
Abstract: A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents.
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Sezer Karaoglu, Jan van Gemert, & Theo Gevers. (2013). Con-text: text detection using background connectivity for fine-grained object classification. In 21ST ACM International Conference on Multimedia (pp. 757–760).
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Eric Amiel. (2005). Visualisation de vaisseaux sanguins (Enric Marti, Ed.). Bachelor's thesis, Université Paul Sabatier Toulouse III, Toulouse.
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Jorge Bernal. (2009). Use of Projection and Back-projection Methods in Bidimensional Computed Tomography Image Reconstruction (Vol. 141). Master's thesis, , Barcelona, Spain.
Abstract: One of the biggest drawbacks related to the use of CT scanners is the cost (in memory and in time) associated. In this project many methods to simulate their functioning, but in a more feasible way (taking an industrial point of view), will be studied.
The main group of techniques that are being used are the one entitled as ’back-projection’. The concept behind is to simulate the X ray emission in CT scans by lines that cross with the image we want to reconstruct.
In the first part of this document euclidean geometry is used to face the tasks of projec- tion and back-projection. After analysing the results achieved it has been proved that this approach does not lead to a fully perfect reconstruction (and also has some other problems related to running time and memory cost). Because of this in the second part of the document ’Filtered Back-projection’ method is introduced in order to improve the results.
Filtered Back-projection methods rely on mathematical transforms (Fourier, Radon) in order to provide more accurate results that can be obtained in much less time. The main cause of this better results is the use of a filtering process before the back-projection in order to avoid high frequency-caused errors.
As a result of this project two different implementations (one for each approach) had been implemented in order to compare their performance.
Keywords: Projection, Back-projection, CT scan, Euclidean geometry, Radon transform
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Jasper Uilings, Koen E.A. van de Sande, Theo Gevers, & Arnold Smeulders. (2013). Selective Search for Object Recognition. IJCV - International Journal of Computer Vision, 104(2), 154–171.
Abstract: This paper addresses the problem of generating possible object locations for use in object recognition. We introduce selective search which combines the strength of both an exhaustive search and segmentation. Like segmentation, we use the image structure to guide our sampling process. Like exhaustive search, we aim to capture all possible object locations. Instead of a single technique to generate possible object locations, we diversify our search and use a variety of complementary image partitionings to deal with as many image conditions as possible. Our selective search results in a small set of data-driven, class-independent, high quality locations, yielding 99 % recall and a Mean Average Best Overlap of 0.879 at 10,097 locations. The reduced number of locations compared to an exhaustive search enables the use of stronger machine learning techniques and stronger appearance models for object recognition. In this paper we show that our selective search enables the use of the powerful Bag-of-Words model for recognition. The selective search software is made publicly available (Software: http://disi.unitn.it/~uijlings/SelectiveSearch.html).
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