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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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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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Elvina Motard, Bogdan Raducanu, Viviane Cadenat, & Jordi Vitria. (2007). Incremental On-Line Topological Map Learning for A Visual Homing Application. In IEEE International Conference on Robotics and Automation (2049–2054).
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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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Karla Lizbeth Caballero, Joel Barajas, & Petia Radeva. (2007). Using Reconstructed IVUS Images for Coronary Plaque Classification. In Engineering in Medicine and Biology Society, 29th Annual International Conference of the IEEE (2167–2170).
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Aura Hernandez-Sabate, Debora Gil, & Albert Teis. (2007). How Do Conservation Laws Define a Motion Suppression Score in In-Vivo Ivus Sequences? In Proc. IEEE Ultrasonics Symp (pp. 2231–2234).
Abstract: Evaluation of arterial tissue biomechanics for diagnosis and treatment of cardiovascular diseases is an active research field in the biomedical imaging processing area. IntraVascular UltraSound (IVUS) is a unique tool for such assessment since it reflects tissue morphology and deformation. A proper quantification and visualization of both properties is hindered by vessel structures misalignments introduced by cardiac dynamics. This has encouraged development of IVUS motion compensation techniques. However, there is a lack of an objective evaluation of motion reduction ensuring a reliable clinical application This work reports a novel score, the Conservation of Density Rate (CDR), for validation of motion compensation in in-vivo pullbacks. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; while results in in vivo pullbacks show its reliability in clinical cases.
Keywords: validation standards; IVUS motion compensation; conservation laws.
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Hugo Berti, Angel Sappa, & Osvaldo Agamennoni. (2007). Autonomous robot navigation with a global and asymptotic convergence. In IEEE International Conference on Robotics and Automation (2712–2717).
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Joan Marti, Jose Miguel Benedi, Ana Maria Mendonça, & Joan Serrat. (2007). Pattern Recognition and Image Analysis (Vol. 6669). LNCS.
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