Debora Gil, Oriol Rodriguez-Leor, Petia Radeva, & Aura Hernandez-Sabate. (2007). Assessing Artery Motion Compensation in IVUS. In Computer Analysis Of Images And Patterns (Vol. 4673, pp. 213–220). Lecture Notes in Computer Science. Heidelberg: Springerlink.
Abstract: Cardiac dynamics suppression is a main issue for visual improvement and computation of tissue mechanical properties in IntraVascular UltraSound (IVUS). Although in recent times several motion compensation techniques have arisen, there is a lack of objective evaluation of motion reduction in in vivo pullbacks. We consider that the assessment protocol deserves special attention for the sake of a clinical applicability as reliable as possible. Our work focuses on defining a quality measure and a validation protocol assessing IVUS motion compensation. On the grounds of continuum mechanics laws we introduce a novel score measuring motion reduction in in vivo sequences. 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; quality measures; IVUS motion compensation; conservation laws; Fourier development
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Bogdan Raducanu, & Jordi Vitria. (2007). Incremental Subspace Learning for Cognitive Visual Processes. In Advances in Brain, Vision and Artificial Intelligence, 2nd International Symposium (Vol. 4729, 214–223). LNCS.
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Carles Fernandez, Pau Baiget, Xavier Roca, & Jordi Gonzalez. (2007). Semantic Annotation of Complex Human Scenes for Multimedia Surveillance. In AI* Artificial Intelligence and Human–Oriented Computing. 10th Congress of the Italian Association for Artificial Intelligence, (Vol. 4733, 698–709). LNCS.
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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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Sergio Escalera, Alicia Fornes, Oriol Pujol, Josep Llados, & Petia Radeva. (2007). Multi-class Binary Object Categorization using Blurred Shape Models. In Progress in Pattern Recognition, Image Analysis and Applications, 12th Iberoamerican Congress on Pattern (Vol. 4756, 773–782). LCNS.
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Carles Fernandez, & Jordi Gonzalez. (2007). Ontology for Semantic Integration in a Cognitive Surveillance System. In Semantic Multimedia, 2nd International Conference on Semantics and Digital Media Technologies (Vol. 4816, 263–263). LNCS.
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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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