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Ferran Diego. (2007). Alignment of Videos Recorded from Moving Vehicles.
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Fadi Dornaika, & Angel Sappa. (2007). Rigid and Non-rigid Face Motion Tracking by Aligning Texture Maps and Stereo 3D Models. PRL - Pattern Recognition Letters, 28(15), 2116–2126.
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Joan Serrat, Ferran Diego, Jose Manuel Alvarez, & Felipe Lumbreras. (2007). Alignment of Videos Recorded from Moving Vehicles. In in 14th International Conference on Image Analysis and Processing, (512–517).
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Joan Serrat, Ferran Diego, Felipe Lumbreras, & Jose Manuel Alvarez. (2007). Synchronization of Video Sequences from Free-moving Cameras. In J. Marti et al. (Ed.), 3rd Iberian Conference on Pattern Recognition and Image Analysis (Vol. 4477, 620–627). LNCS.
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Antonio Lopez, Joan Serrat, Cristina Cañero, & Felipe Lumbreras. (2007). Robust Lane Lines Detection and Quantitative Assessment. In J. Marti et al (Ed.), 3rd Iberian Conference on Pattern Recognition and Image Analysis (Vol. 4477, 274–281). LNCS.
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Meritxell Vinyals, Arnau Ramisa, & Ricardo Toledo. (2007). An Evaluation of an Object Recognition Schema using Multiple Region Detectors. In Artificial Intelligence Research and Development, 163:213–222, ISBN: 978–1–58603–798–7, Proceedings of the 10th International Conference of the ACIA (CCIA’07).
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Antonio Lopez, W. Niessen, Joan Serrat, K. Nikolay, B. Ter Haar Romeny, Juan J. Villanueva, et al. (2000). New improvements in the multiscale analysis of trabecular bone patterns. In Pattern Recognition and Applications (pp. 251–260). IOS Press.
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Angel Sappa, Fadi Dornaika, David Geronimo, & Antonio Lopez. (2007). Efficient On-Board Stereo Vision Pose Estimation. In Computer Aided Systems Theory, Selected paper from (Vol. 4739, 1183–1190). LNCS.
Abstract: This paper presents an efficient technique for real time estimation of on-board stereo vision system pose. The whole process is performed in the Euclidean space and consists of two stages. Initially, a compact representation of the original 3D data points is computed. Then, a RANSAC based least squares approach is used for fitting a plane to the 3D road points. Fast RANSAC fitting is obtained by selecting points according to a probability distribution function that takes into account the density of points at a given depth. Finally, stereo camera position
and orientation—pose—is computed relative to the road plane. The proposed technique is intended to be used on driver assistance systems for applications such as obstacle or pedestrian detection. A real time performance is reached. Experimental results on several environments and comparisons with a previous work are presented.
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Angel Sappa, Rosa Herrero, Fadi Dornaika, David Geronimo, & Antonio Lopez. (2007). Road Approximation in Euclidean and v-Disparity Space: A Comparative Study. In Computer Aided Systems Theory, (Vol. 4739, 1105–1112). LNCS.
Abstract: This paper presents a comparative study between two road approximation techniques—planar surfaces—from stereo vision data. The first approach is carried out in the v-disparity space and is based on a voting scheme, the Hough transform. The second one consists in computing the best fitting plane for the whole 3D road data points, directly in the Euclidean space, by using least squares fitting. The comparative study is initially performed over a set of different synthetic surfaces
(e.g., plane, quadratic surface, cubic surface) digitized by a virtual stereo head; then real data obtained with a commercial stereo head are used. The comparative study is intended to be used as a criterion for fining the best technique according to the road geometry. Additionally, it highlights common problems driven from a wrong assumption about the scene’s prior knowledge.
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Daniel Ponsa, & Antonio Lopez. (2007). Cascade of Classifiers for Vehicle Detection. In Advanced Concepts for Intelligent Vision Systems, LNCS 4678, volume 1, pp. 980–989.
Keywords: vehicle detection
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Angel Sappa, Rosa Herrero, Fadi Dornaika, David Geronimo, & Antonio Lopez. (2007). Road Approximation in Euclidean and v-Disparity Space: A Comparative Study. In EUROCAST2007, Workshop on Cybercars and Intelligent Vehicles (368–369).
Abstract: This paper presents a comparative study between two road approximation techniques—planar surfaces—from stereo vision data. The first approach is carried out in the v-disparity space and is based on a voting scheme, the Hough transform. The second one consists in computing the best fitting plane for the whole 3D road data points, directly in the Euclidean space, by using least squares fitting. The comparative study is initially performed over a set of different synthetic surfaces
(e.g., plane, quadratic surface, cubic surface) digitized by a virtual stereo head; then real data obtained with a commercial stereo head are used. The comparative study is intended to be used as a criterion for fining the best technique according to the road geometry. Additionally, it highlights common problems driven from a wrong assumption about the scene’s prior knowledge.
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Javier Jimenez, Antonio Lopez, & Joan Serrat. (2007). Un enfoque ABP aplicado a Ingenieria del Software.
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Angel Sappa, & Boris X. Vintimilla. (2008). Edge Point Linking by Means of Global and Local Schemes. In E. Damiani (Ed.), in Signal Processing for Image Enhancement and Multimedia Processing (Vol. 11, 115–125). Springer.
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Carme Julia, Angel Sappa, Felipe Lumbreras, Joan Serrat, & Antonio Lopez. (2008). Rank Estimation in 3D Multibody Motion Segmentation. Electronic Letters, 44(4), 279–280.
Abstract: A novel technique for rank estimation in 3D multibody motion segmentation is proposed. It is based on the study of the frequency spectra of moving rigid objects and does not use or assume a prior knowledge of the objects contained in the scene (i.e. number of objects and motion). The significance of rank estimation on multibody motion segmentation results is shown by using two motion segmentation algorithms over both synthetic and real data.
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Joan Serrat, & Antonio Lopez. (2006). Una experiencia de Enginyeria del Software amb ABP.
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