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Niki Aifanti, Angel Sappa, N. Grammalidis, & Sotiris Malassiotis. (2005). Human Motion Tracking and Recognition. In Encyclopedia of Information Science and Technology, 1(5):1355–1360.
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Angel Sappa, Niki Aifanti, Sotiris Malassiotis, & N. Grammalidis. (2005). Survey of 3D Human Body Representations. In Encyclopedia of Information Science and Technology, 1(5):2696–2701.
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Jordi Gonzalez, J. Varona, Xavier Roca, & Juan J. Villanueva. (2004). Situation Graph Trees for Human Behavior Modeling.
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Zhong Jin, & Franck Davoine. (2004). Orthogonal ICA Representation Of Images.
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Oriol Ramos Terrades, Salvatore Tabbone, L. Wendling, & Ernest Valveny. (2004). Symbol Recognition based on a Multiresolution Analysis of the Radon Transform.
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Ernest Valveny, & Philippe Dosch. (2004). Symbol Recognition Contest: A Synthesis.
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Ernest Valveny, & Philippe Dosch. (2004). Performance Evaluation of Symbol Recognition. In A. D.(E.) S. Marinai (Ed.), Document Analysis Systems (Vol. 3163, 354–365).
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Oriol Ramos Terrades, & Ernest Valveny. (2004). Indexing Technical Symbols Using Ridgelets Transform.
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Oriol Pujol, & Petia Radeva. (2004). Texture Segmentation by Statistical Deformable Models. IJIG - International Journal of Image and Graphics, 433–452.
Abstract: Deformable models have received much popularity due to their ability to include high-level knowledge on the application domain into low-level image processing. Still, most proposed active contour models do not sufficiently profit from the application information and they are too generalized, leading to non-optimal final results of segmentation, tracking or 3D reconstruction processes. In this paper we propose a new deformable model defined in a statistical framework to segment objects of natural scenes. We perform a supervised learning of local appearance of the textured objects and construct a feature space using a set of co-occurrence matrix measures. Linear Discriminant Analysis allows us to obtain an optimal reduced feature space where a mixture model is applied to construct a likelihood map. Instead of using a heuristic potential field, our active model is deformed on a regularized version of the likelihood map in order to segment objects characterized by the same texture pattern. Different tests on synthetic images, natural scene and medical images show the advantages of our statistic deformable model.
Keywords: Texture segmentation, parametric active contours, statistic snakes
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Carme Julia. (2004). Motion segmentation through factorization. Application to night driving assistance.
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Raul Chaves. (2004). Sistema de identificacion mediante huellas dactilares.
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Oriol Martinez. (2004). Semantic Retrieval of Memory Color Content.
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Jordi Vitria, Petia Radeva, & I. Aguilo. (2004). Recent Advances in Artificial Intelligence Research and Development. In Frontiers in Artificial Intelligence and Applications, 113, J. Vitria, P. Radeva, I. Aguilo (Eds.), ISBN: 1–58603–466–9.
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David Masip, & Jordi Vitria. (2004). Boosted Linear Projections for Discriminant Analysis.
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Oriol Pujol. (2004). A semi-Supervised Statistical Framework and Generative Snakes for IVUS Analysis (Petia Radeva, Ed.). Ph.D. thesis, , .
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