Judit Martinez, & F. Thomas. (2002). Efficient Computation of Local Geometric Moments. IEEE Transactions on Image Porcessing, (IF: 2.553), 11(9), 1102–1111.
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Xavier Otazu, M. Ribo, M. Peracaula, J.M. Paredes, & J. Nuñez. (2002). Detection of superimposed periodic signals using wavelets. Monthly Notices of the Royal Astronomical Society, 333, 2: 365–372 (IF: 4.671).
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A. Pujol, & Juan J. Villanueva. (2002). A supervised Modification of the Hausdorff distance for visual shape classification. International Journal of Pattern Recognition and Artificial Intelligence, 349–359.
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J.M. Sanchez, X. Binefa, & Jordi Vitria. (2002). Shot Partitioning Based Recognition of Tv Commercials. Multimedia Tools and Applications, 18: 233–247, Kluwer Academic Publishers (IF: 0.421).
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Gemma Sanchez, Josep Llados, & K. Tombre. (2002). A mean string algorithm to compute the average among a set of 2D shapes. PRL - Pattern Recognition Letters, 23(1-3), 203–214.
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Juan J. Villanueva. (2002). Visualization, Imaging and Image Processing..
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M. Bressan, & Jordi Vitria. (2002). Feature Subset Selection in an ICA Space.
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M. Bressan, & Jordi Vitria. (2002). Improving Naive Bayes using Class Conditional ICA.
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David Vazquez, David Geronimo, & Antonio Lopez. (2009). The effect of the distance in pedestrian detection (Vol. 149). Master's thesis, , .
Abstract: Pedestrian accidents are one of the leading preventable causes of death. In order to reduce the number of accidents, in the last decade the pedestrian protection systems have been introduced, a special type of advanced driver assistance systems, in witch an on-board camera explores the road ahead for possible collisions with pedestrians in order to warn the driver or perform braking actions. As a result of the variability of the appearance, pose and size, pedestrian detection is a very challenging task. So many techniques, models and features have been proposed to solve the problem. As the appearance of pedestrians varies signicantly as a function of distance, a system based on multiple classiers specialized on diferent depths is likely to improve the overall performance with respect to a typical system based on a general detector. Accordingly, the main aim of this work is to explore the eect of the distance in pedestrian detection. We have evaluated three pedestrian detectors (HOG, HAAR and EOH) in two dierent databases (INRIA and Daimler09) for two dierent sizes (small and big). By a extensive set of experiments we answer to questions like which datasets and evaluation methods are the most adequate, which is the best method for each size of the pedestrians and why or how do the method optimum parameters vary with respect to the distance
Keywords: Pedestrian Detection
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David Guillamet, & Jordi Vitria. (2002). Non-negative Matrix Factorization for Face Recognition..
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Daniel Ponsa, & Xavier Roca. (2002). A Novel Approach to Generate Multiple Shape Models..
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Petia Radeva, M. Bressan, A. Tovar, & Jordi Vitria. (2002). Bayesian Classification for Inspection of Industrial Products..
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Francesc Tous, Agnes Borras, Robert Benavente, Ramon Baldrich, Maria Vanrell, & Josep Llados. (2002). Textual Descriptors for browsing people by visual appearence. In 5è. Congrés Català d’Intel·ligència Artificial CCIA.
Abstract: This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building.
Keywords: Image retrieval, textual descriptors, colour naming, colour normalization, graph matching.
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M. Bressan, & Jordi Vitria. (2002). Independent Component Analysis and Naïve Bayes Classification. In Proceedings of the Second IASTED International Conference Visualilzation, Imaging and Image Proceesing VIIP 2002: 496–501..
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Robert Benavente, Francesc Tous, Ramon Baldrich, & Maria Vanrell. (2002). Statical Modelling of a Colour Naming Space..
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