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Author |
Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis |
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Title |
Prior Knowledge Based Motion Model Representation |
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2005 |
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Electronic Letters on Computer Vision and Image Analysis, Special Issue on Articulated Motion & Deformable Objects, 5(3):55–67 (Electronic Letters: IF: 1.016) |
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ADAS @ adas @ SAM2005b |
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539 |
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Author |
Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis |
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Title |
Prior Knowledge Based Motion Model Representation |
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Book Chapter |
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2009 |
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Progress in Computer Vision and Image Analysis |
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16 |
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Horst Bunke; JuanJose Villanueva; Gemma Sanchez |
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ADAS @ adas @ SAM2009 |
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1235 |
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Author |
Angel Sappa; Niki Aifanti; N. Grammalidis; Sotiris Malassiotis |
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Title |
Advances in Vision-Based Human Body Modeling |
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2004 |
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3D Modeling & Animation: Systhesis and Analysis Techniques for the Human Body |
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1-26 |
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N. Sarris and M. Strintzis. |
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1-59140-299-9 |
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ADAS @ adas @ SAG2004a |
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458 |
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Author |
Angel Sappa; Mohammad Rouhani |
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Title |
Efficient Distance Estimation for Fitting Implicit Quadric Surfaces |
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2009 |
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16th IEEE International Conference on Image Processing |
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3521–3524 |
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This paper presents a novel approach for estimating the shortest Euclidean distance from a given point to the corresponding implicit quadric fitting surface. It first estimates the orthogonal orientation to the surface from the given point; then the shortest distance is directly estimated by intersecting the implicit surface with a line passing through the given point according to the estimated orthogonal orientation. The proposed orthogonal distance estimation is easily obtained without increasing computational complexity; hence it can be used in error minimization surface fitting frameworks. Comparisons of the proposed metric with previous approaches are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. Surfaces fitted by using the proposed geometric distance estimation and state of the art metrics are presented to show the viability of the proposed approach. |
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Cairo, Egypt |
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1522-4880 |
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978-1-4244-5653-6 |
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ICIP |
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ADAS @ adas @ SaR2009 |
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1232 |
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Author |
Angel Sappa; M.A. Garcia |
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Title |
Hierarchical Clustering of 3D Objects and its Application to Minimum Distance Computation |
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Conference Article |
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2004 |
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IEEE International Conference on Robotics & Automation, 5287–5292, New Orleans, LA (USA), ISBN: 0–7803–8232–3 |
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New Orleans, LA, USA |
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ADAS @ adas @ SaG2004b |
Serial |
459 |
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Author |
Angel Sappa; M.A. Garcia |
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Title |
Generating compact representations of static scenes by means of 3D object hierarchies |
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2007 |
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The Visual Computer, 23(2): 143–154 |
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ADAS @ adas @ SaG2007a |
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798 |
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Author |
Angel Sappa; M.A. Garcia |
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Title |
Coarse-to-Fine Approximation of Range Images with Bounded Error Adaptive Triangular Meshes |
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2007 |
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Journal of Electronic Imaging, 16(2), 023010(11 pages) |
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ADAS @ adas @ SaG2007b |
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802 |
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Author |
Angel Sappa; M.A. Garcia |
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Title |
Incremental Integration of Multiresolution Range Images |
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2007 |
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The imaging science journal. Vol. 55, No. 3 pp. 127–139 |
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ADAS @ adas @ SaG2007d |
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812 |
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Author |
Angel Sappa; M.A. Garcia |
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Title |
Aprendiendo a recrear la realidad en 3D |
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2007 |
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UAB Divulga, Revista de Divulgacion Cientifica |
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spreading |
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ADAS @ adas @ SaG2007c |
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1470 |
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Author |
Angel Sappa; Jordi Vitria |
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Title |
Multimodal Interaction in Image and Video Applications |
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2013 |
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Multimodal Interaction in Image and Video Applications |
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48 |
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Book Series Intelligent Systems Reference Library |
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Springer Berlin Heidelberg |
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1868-4394 |
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978-3-642-35931-6 |
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ADAS; OR;MV |
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Admin @ si @ SaV2013 |
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2199 |
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Author |
Angel Sappa; George A. Triantafyllid |
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Computer Graphics and Imaging |
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2012 |
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Computer Graphics and Imaging |
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Crete, Greece |
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978-0-88986-921-9 |
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Admin @ si @ Sap2012 |
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2067 |
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Author |
Angel Sappa; Fadi Dornaika; David Geronimo; Antonio Lopez |
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Title |
Efficient On-Board Stereo Vision Pose Estimation |
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2007 |
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Computer Aided Systems Theory, Selected paper from |
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4739 |
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1183–1190 |
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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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Las Palmas de Gran Canaria (Spain) |
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EUROCAST |
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ADAS |
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ADAS @ adas @ SDG2007b |
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916 |
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Angel Sappa; Fadi Dornaika; David Geronimo; Antonio Lopez |
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Title |
Registration-based Moving Object Detection from a Moving Camera |
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2008 |
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IROS2008 2nd Workshop on Perception, Planning and Navigation for Intelligent Vehicles |
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65–69 |
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This paper presents a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three stages. Initially, feature points are extracted and tracked through consecutive frames. Then, a RANSAC based approach is used for registering
two 3D point sets with known correspondences by means of the quaternion method. Finally, the computed 3D rigid displacement is used to map two consecutive frames into the same coordinate system. Moving objects correspond to those areas with large registration errors. Experimental results, in different scenarios, show the viability of the proposed approach. |
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Nice (France) |
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ADAS @ adas @ SDG2008 |
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1017 |
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Angel Sappa; Fadi Dornaika; Daniel Ponsa; David Geronimo; Antonio Lopez |
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An Efficient Approach to Onboard Stereo Vision System Pose Estimation |
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2008 |
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IEEE Transactions on Intelligent Transportation Systems |
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TITS |
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9 |
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3 |
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476–490 |
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Camera extrinsic parameter estimation, ground plane estimation, onboard stereo vision system |
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This paper presents an efficient technique for estimating the pose of an onboard stereo vision system relative to the environment’s dominant surface area, which is supposed to be the road surface. Unlike previous approaches, it can be used either for urban or highway scenarios since it is not based on a specific visual traffic feature extraction but on 3-D raw data points. The whole process is performed in the Euclidean space and consists of two stages. Initially, a compact 2-D representation of the original 3-D data points is computed. Then, a RANdom SAmple Consensus (RANSAC) based least-squares approach is used to fit a plane to the road. Fast RANSAC fitting is obtained by selecting points according to a probability function that takes into account the density of points at a given depth. Finally, stereo camera height and pitch angle are computed related to the fitted road plane. The proposed technique is intended to be used in driverassistance systems for applications such as vehicle or pedestrian detection. Experimental results on urban environments, which are the most challenging scenarios (i.e., flat/uphill/downhill driving, speed bumps, and car’s accelerations), are presented. These results are validated with manually annotated ground truth. Additionally, comparisons with previous works are presented to show the improvements in the central processing unit processing time, as well as in the accuracy of the obtained results. |
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IEEE |
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ADAS @ adas @ SDP2008 |
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Angel Sappa; Fadi Dornaika |
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An Edge-Based Approach to Motion Detection |
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2006 |
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6th International Conference on Computational Science (ICCS´06), LNCS 3991:563–570 |
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Reading (United Kingdom) |
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ADAS @ adas @ SaD2006 |
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654 |
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