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David Geronimo, Angel Sappa, & Antonio Lopez. (2010). Stereo-based Candidate Generation for Pedestrian Protection Systems. In Binocular Vision: Development, Depth Perception and Disorders (189–208). NOVA Publishers.
Abstract: This chapter describes a stereo-based algorithm that provides candidate image windows to a latter 2D classification stage in an on-board pedestrian detection system. The proposed algorithm, which consists of three stages, is based on the use of both stereo imaging and scene prior knowledge (i.e., pedestrians are on the ground) to reduce the candidate searching space. First, a successful road surface fitting algorithm provides estimates on the relative ground-camera pose. This stage directs the search toward the road area thus avoiding irrelevant regions like the sky. Then, three different schemes are used to scan the estimated road surface with pedestrian-sized windows: (a) uniformly distributed through the road surface (3D); (b) uniformly distributed through the image (2D); (c) not uniformly distributed but according to a quadratic function (combined 2D-3D). Finally, the set of candidate windows is reduced by analyzing their 3D content. Experimental results of the proposed algorithm, together with statistics of searching space reduction are provided.
Keywords: Pedestrian Detection
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Sergio Escalera, Oriol Pujol, Eric Laciar, Jordi Vitria, Esther Pueyo, & Petia Radeva. (2010). Classification of Coronary Damage in Chronic Chagasic Patients. In M. H.(eds) V. Sgurev (Ed.), Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence (Vol. 299, pp. 461–478). Springer-Verlag.
Abstract: Post Conference IEEE-IS 2008
The Chagas’ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the chagas’ disease, it is important to detect and measure the coronary damage of the patient. In this paper,
we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of Error-Correcting Output Codes (ECOC)is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs.
Keywords: Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding
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Thierry Brouard, A. Delaplace, Muhammad Muzzamil Luqman, H. Cardot, & Jean-Yves Ramel. (2010). Design of Evolutionary Methods Applied to the Learning of Bayesian Nerwork Structures. In Ahmed Rebai (Ed.), Bayesian Network (pp. 13–37). Sciyo.
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Jaume Garcia, Petia Radeva, & Francesc Carreras. (2004). Combining Spectral and Active Shape methods to Track Tagged MRI. In Recent Advances in Artificial Intelligence Research and Development (pp. 37–44). IOS Press.
Abstract: Tagged magnetic resonance is a very usefull and unique tool that provides a complete local and global knowledge of the left ventricle (LV) motion. In this article we introduce a method capable of tracking and segmenting the LV. Spectral methods are applied in order to obtain the so called HARP images which encode information about movement and are the base for LV point-tracking. For segmentation we use Active Shapes (ASM) that model LV shape variation in order to overcome possible local misplacements of the boundary. We finally show experiments on both synthetic and real data which appear to be very promising.
Keywords: MR; tagged MR; ASM; LV segmentation; motion estimation.
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Jaume Garcia, Debora Gil, & Aura Hernandez-Sabate. (2010). Endowing Canonical Geometries to Cardiac Structures. In O. Camara, M. Pop, K. Rhode, M. Sermesant, N. Smith, & A. Young (Eds.), Statistical Atlases And Computational Models Of The Heart (Vol. 6364, pp. 124–133). LNCS. Springer Berlin / Heidelberg.
Abstract: International conference on Cardiac electrophysiological simulation challenge
In this paper, we show that canonical (shape-based) geometries can be endowed to cardiac structures using tubular coordinates defined over their medial axis. We give an analytic formulation of these geometries by means of B-Splines. Since B-Splines present vector space structure PCA can be applied to their control points and statistical models relating boundaries and the interior of the anatomical structures can be derived. We demonstrate the applicability in two cardiac structures, the 3D Left Ventricular volume, and the 2D Left-Right ventricle set in 2D Short Axis view.
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Ole Vilhelm-Larsen, Petia Radeva, & Enric Marti. (1995). Guidelines for choosing optimal parameters of elasticity for snakes. In Computer Analysis Of Images And Patterns (Vol. 970, pp. 106–113). LNCS.
Abstract: This paper proposes a guidance in the process of choosing and using the parameters of elasticity of a snake in order to obtain a precise segmentation. A new two step procedure is defined based on upper and lower bounds on the parameters. Formulas, by which these bounds can be calculated for real images where parts of the contour may be missing, are presented. Experiments on segmentation of bone structures in X-ray images have verified the usefulness of the new procedure.
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Josep Llados, Jaime Lopez-Krahe, & Enric Marti. (1997). A system to understand hand-drawn floor plans using subgraph isomorphism and Hough transform. In Machine Vision and Applications (Vol. 10, pp. 150–158).
Abstract: Presently, man-machine interface development is a widespread research activity. A system to understand hand drawn architectural drawings in a CAD environment is presented in this paper. To understand a document, we have to identify its building elements and their structural properties. An attributed graph structure is chosen as a symbolic representation of the input document and the patterns to recognize in it. An inexact subgraph isomorphism procedure using relaxation labeling techniques is performed. In this paper we focus on how to speed up the matching. There is a building element, the walls, characterized by a hatching pattern. Using a straight line Hough transform (SLHT)-based method, we recognize this pattern, characterized by parallel straight lines, and remove from the input graph the edges belonging to this pattern. The isomorphism is then applied to the remainder of the input graph. When all the building elements have been recognized, the document is redrawn, correcting the inaccurate strokes obtained from a hand-drawn input.
Keywords: Line drawings – Hough transform – Graph matching – CAD systems – Graphics recognition
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Josep Llados, Ernest Valveny, Gemma Sanchez, & Enric Marti. (2002). Symbol recognition: current advances and perspectives. In Dorothea Blostein and Young- Bin Kwon (Ed.), Graphics Recognition Algorithms And Applications (Vol. 2390, pp. 104–128). LNCS. Springer-Verlag.
Abstract: The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.
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Josep Llados, Gemma Sanchez, & Enric Marti. (1998). A string based method to recognize symbols and structural textures in architectural plans. In Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers (Vol. 1389, pp. 91–103). LNCS. Springer Link.
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.
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Josep Llados, Ernest Valveny, & Enric Marti. (2000). Symbol Recognition in Document Image Analysis: Methods and Challenges. In Recent Research Developments in Pattern Recognition, Transworld Research Network, (Vol. 1, 151–178.).
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Enric Marti, Jordi Regincos, Juan Jose Villanueva, & Jaime Lopez-Krahe. (1994). Line drawing interpretation as polyhedral objects to man-machine interaction in CAD systems. In Advances in Pattern Recognition and Image Analysis, (pp. 158–169). World Scientific Pub.
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Misael Rosales, Petia Radeva, Oriol Rodriguez, & Debora Gil. (2005). Suppression of IVUS Image Rotation. A Kinematic Approach. In Monica Andres and Hernandez Petia and Santos A. and R. Frangi (Ed.), Functional Imaging and Modeling of the Heart (Vol. 3504, pp. 889–892). LNCS, 3504. Springer Berlin / Heidelberg.
Abstract: IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology.
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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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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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Jorge Bernal, Fernando Vilariño, & F. Javier Sanchez. (2011). Towards Intelligent Systems for Colonoscopy. In Paul Miskovitz (Ed.), Colonoscopy (Vol. 1, pp. 257–282). Intech.
Abstract: In this chapter we present tools that can be used to build intelligent systems for colonoscopy.
The idea is, by using methods based on computer vision and artificial intelligence, add significant value to the colonoscopy procedure. Intelligent systems are being used to assist in other medical interventions
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