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Cristina Cañero; Petia Radeva; Oriol Pujol; Ricardo Toledo; Debora Gil; J. Saludes; Juan J. Villanueva; B. Garcia del Blanco; Josefina Mauri; Eduard Fernandez-Nofrerias; J.A. Gomez-Hospital; E. Iraculis; J. Comin; C. Quiles; F. Jara; A. Cequier; E.Esplugas |
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Three-dimensional reconstruction and quantification of the coronary tree using intravascular ultrasound images |
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Conference Article |
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1999 |
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Proceedings of International Conference on Computer in Cardiology (CIC´99) |
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In this paper we propose a new Computer Vision technique to reconstruct the vascular wall in space using a deformable model-based technique and compounding methods, based in biplane angiography and intravascular ultrasound data jicsion. It is also proposed a generalpurpose three-dimensional guided interpolation method. The three dimensional centerline of the vessel is reconstructed from geometrically corrected biplane angiographies using automatic segmentation methods and snakes. The IVUS image planes are located in the threedimensional space and correctly oriented. A led interpolation method based in B-SurJaces and snakes isused to fill the gaps among image planes |
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CINC99 |
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MILAB;RV;IAM;ADAS;HuPBA |
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IAM @ iam @ CRP1999b |
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1492 |
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M.Gomez; Josefina Mauri; Eduard Fernandez-Nofrerias; Oriol Rodriguez-Leon; Carme Julia; Debora Gil; Petia Radeva |
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Reconstrucción de un modelo espacio-temporal de la luz del vaso a partir de secuencias de ecografía intracoronaria |
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Conference Article |
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2002 |
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XXXVIII Congreso Nacional de la Sociedad Española de Cardiología. |
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IAM;ADAS;MILAB |
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IAM @ iam @ GMF2002d |
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1516 |
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Josefina Mauri; Eduard Fernandez-Nofrerias; B. Garcia del Blanco; E. Iraculis; J.A. Gomez-Hospital; J. Comin; M.A. Sanchez Corral; F. Jara; A. Cequier; E. Esplugas; Debora Gil; J. Saludes; Petia Radeva; Ricardo Toledo; Juan J.Villanueva |
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Moviment del vas en l anàlisi d imatges d ecografia intracoronària: un model matemàtic |
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Conference Article |
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2000 |
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Congrés de la Societat Catalana de Cardiologia. |
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IAM;RV;ISE;MILAB;ADAS |
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IAM @ iam @ MNG2000 |
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1621 |
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Josefina Mauri; Eduard Fernandez-Nofrerias; J. Comin; B. Garcia del Blanco; E. Iraculis; J.A. Gomez-Hospital; P. Valdovinos; F. Jara; A. Cequier; E. Esplugas; Oriol Pujol; Cristina Cañero; Debora Gil; Petia Radeva; Ricardo Toledo |
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Avaluació del Conjunt Stent/Artèria mitjançant ecografia intracoronària: lentorn informàtic |
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2000 |
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Congrés de la Societat Catalana de Cardiologia. |
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IAM;RV;MILAB;ADAS;HuPBA |
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IAM @ iam @ MNC2000 |
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1622 |
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Oriol Rodriguez-Leon; Josefina Mauri; Eduard Fernandez-Nofrerias; M.Gomez; Antonio Tovar; L.Cano; C.Diego; Carme Julia; Vicente del Valle; Debora Gil; Petia Radeva |
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Ecografia Intracoronària: Segmentació Automàtica de area de la llum |
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2002 |
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XXXVIII Congreso Nacional de la Sociedad Española de Cardiología. |
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IAM;ADAS;MILAB |
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IAM @ iam @ RMF2002 |
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1638 |
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Joan Serrat; Enric Marti |
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Elastic matching using interpolation splines |
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1991 |
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IV Spanish Symposium of Pattern Recognition and image Analysis |
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ADAS;IAM; |
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IAM @ iam @ SMV1991 |
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1651 |
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Andrew Nolan; Daniel Serrano; Aura Hernandez-Sabate; Daniel Ponsa; Antonio Lopez |
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Obstacle mapping module for quadrotors on outdoor Search and Rescue operations |
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2013 |
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International Micro Air Vehicle Conference and Flight Competition |
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Obstacle avoidance remains a challenging task for Micro Aerial Vehicles (MAV), due to their limited payload capacity to carry advanced sensors. Unlike larger vehicles, MAV can only carry light weight sensors, for instance a camera, which is our main assumption in this work. We explore passive monocular depth estimation and propose a novel method Position Aided Depth Estimation
(PADE). We analyse PADE performance and compare it against the extensively used Time To Collision (TTC). We evaluate the accuracy, robustness to noise and speed of three Optical Flow (OF) techniques, combined with both depth estimation methods. Our results show PADE is more accurate than TTC at depths between 0-12 meters and is less sensitive to noise. Our findings highlight the potential application of PADE for MAV to perform safe autonomous navigation in
unknown and unstructured environments. |
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Toulouse; France; September 2013 |
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IMAV |
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ADAS; 600.054; 600.057;IAM |
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Admin @ si @ NSH2013 |
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2371 |
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David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin |
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Cool world: domain adaptation of virtual and real worlds for human detection using active learning |
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2011 |
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NIPS Domain Adaptation Workshop: Theory and Application |
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NIPS-DA |
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Pedestrian Detection; Virtual; Domain Adaptation; Active Learning |
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Image based human detection is of paramount interest for different applications. The most promising human detectors rely on discriminatively learnt classifiers, i.e., trained with labelled samples. However, labelling is a manual intensive task, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, in Marin et al. we have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera and the same type of scenario. Accordingly, in Vazquez et al. we cast the problem as one of supervised domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we use an active learning technique. Thus, ultimately our human model is learnt by the combination of virtual- and real-world labelled samples which, to the best of our knowledge, was not done before. Here, we term such combined space cool world. In this extended abstract we summarize our proposal, and include quantitative results from Vazquez et al. showing its validity. |
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Granada, Spain |
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Granada, Spain |
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English |
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English |
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DA-NIPS |
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ADAS @ adas @ VLP2011b |
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1756 |
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Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras |
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The IIIA30 MObile Robot Object Recognition Datset |
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2011 |
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11th Portuguese Robotics Open |
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Object perception is a key feature in order to make mobile robots able to perform high-level tasks. However, research aimed at addressing the constraints and limitations encountered in a mobile robotics scenario, like low image resolution, motion blur or tight computational constraints, is still very scarce. In order to facilitate future research in this direction, in this work we present an object detection and recognition dataset acquired using a mobile robotic platform. As a baseline for the dataset, we evaluated the cascade of weak classifiers object detection method from Viola and Jones. |
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Lisboa |
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Robotica |
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RV;ADAS |
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Admin @ si @ RAV2011 |
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1777 |
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G.D. Evangelidis; Ferran Diego; Joan Serrat; Antonio Lopez |
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Slice Matching for Accurate Spatio-Temporal Alignment |
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2011 |
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In ICCV Workshop on Visual Surveillance |
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video alignment |
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Video synchronization and alignment is a rather recent topic in computer vision. It usually deals with the problem of aligning sequences recorded simultaneously by static, jointly- or independently-moving cameras. In this paper, we investigate the more difficult problem of matching videos captured at different times from independently-moving cameras, whose trajectories are approximately coincident or parallel. To this end, we propose a novel method that pixel-wise aligns videos and allows thus to automatically highlight their differences. This primarily aims at visual surveillance but the method can be adopted as is by other related video applications, like object transfer (augmented reality) or high dynamic range video. We build upon a slice matching scheme to first synchronize the sequences, while we develop a spatio-temporal alignment scheme to spatially register corresponding frames and refine the temporal mapping. We investigate the performance of the proposed method on videos recorded from vehicles driven along different types of roads and compare with related previous works. |
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Admin @ si @ EDS2011; ADAS @ adas @ eds2011a |
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1861 |
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