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Author |
Carme Julia; Joan Serrat; Antonio Lopez; Felipe Lumbreras; Daniel Ponsa |
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Title |
Motion segmentation through factorization. Application to night driving assistance |
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Miscellaneous |
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2006 |
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International Conference on Computer Vision Theory and Applications, (2) |
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ADAS @ adas @ JSL2006a |
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638 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
Factorization with Missing and Noisy Data |
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Conference Article |
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2006 |
Publication |
6th International Conference on Computational Science |
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ICCS´06 |
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LNCS 3991 |
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555–562 |
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Reading (United Kingdom) |
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ADAS @ adas @ JSL2006b |
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653 |
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Author |
Angel Sappa; Fadi Dornaika |
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Title |
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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ADAS |
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ADAS @ adas @ SaD2006 |
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654 |
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Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez |
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Title |
On-board camera extrinsic parameter estimation |
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Year |
2006 |
Publication |
Electronics Letters |
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EL |
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42 |
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13 |
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745–746 |
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An efficient technique for real-time estimation of camera extrinsic parameters is presented. It is intended to be used on on-board vision systems for driving assistance applications. The proposed technique is based on the use of a commercial stereo vision system that does not need any visual feature extraction. |
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IEE |
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ADAS |
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no |
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ADAS @ adas @ SGD2006a |
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655 |
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Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez |
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Title |
Real Time Vehicle Pose Using On-Board Stereo Vision System |
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Conference Article |
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Year |
2006 |
Publication |
International Conference on Image Analysis and Recognition |
Abbreviated Journal |
ICIAR |
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Issue |
LNCS 4142 |
Pages |
205–216 |
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This paper presents a robust technique for a real time estimation of both camera’s position and orientation—referred as pose. A commercial stereo vision system is used. Unlike previous approaches, it can be used either for urban or highway scenarios. The proposed technique consists of two stages. Initially, a compact 2D representation of the original 3D data points is computed. Then, a RANSAC based least squares approach is used for fitting a plane to the road. At the same time,
relative camera’s position and orientation are computed. The proposed technique is intended to be used on a driving assistance scheme for applications such as obstacle or pedestrian detection. Experimental results on urban environments with different road geometries are presented. |
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ADAS |
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ADAS @ adas @ SGD2006b |
Serial |
671 |
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Author |
David Geronimo; Angel Sappa; Antonio Lopez; Daniel Ponsa |
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Title |
Pedestrian Detection Using AdaBoost Learning of Features and Vehicle Pitch Estimation |
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Miscellaneous |
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Year |
2006 |
Publication |
6th IASTED International Conference on Visualization, Imaging and Image Processing |
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VIIP |
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400–405 |
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ADAS, pedestrian detection, adaboost learning, pitch estimation, haar wavelets, edge orientation histograms. |
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In this paper we propose a combination of different Haar filter sets and Edge Orientation Histograms (EOH) in order to learn a model for pedestrian detection. As we will show, with the addition of EOH we obtain better ROCs than using Haar filters alone. Hence, a model consisting of discriminant features, selected by AdaBoost, is applied at pedestrian-sized image windows in order to perform
the classification. Additionally, taking into account the final application, a driver assistance system with realtime requirements, we propose a novel stereo-based camera pitch estimation to reduce the number of explored windows.
With this approach, the system can work in urban roads, as will be illustrated by current results. |
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Palma de Mallorca (Spain) |
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ADAS |
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ADAS @ adas @ GSL2006 |
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672 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
3D Face Tracking using Appearance Registration and Robust Iterative Closest Point Algorithm |
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2006 |
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21st International Symposium on Computer and Information Sciences (ISCIS´06), LNCS 4263: 532–541 |
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Istanbul (Turkey) |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ DoS2006d |
Serial |
688 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Rigid and Non-Rigid Face Motion Tracking by Aligning Texture Maps and Stereo-Based 3D Models |
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Book Chapter |
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2006 |
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8th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS´06), LNCS 4179: 675–684 |
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Antwerp (Belgium) |
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ADAS |
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ADAS @ adas @ DoS2006c |
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689 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
3D Motion from Image Derivatives using the Least Trimmed Square Regression |
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Book Chapter |
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2006 |
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International Workshop on Intelligent Computing in Pattern Analysis/Synthesis (IWICPAS´06), LNCS 4153: 76–84 |
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Xi'an (China) |
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ADAS |
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ADAS @ adas @ DoS2006b |
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690 |
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Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
An Iterative Multiresolution Scheme for SFM |
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Conference Article |
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2006 |
Publication |
International Conference on Image Analysis and Recognition |
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ICIAR 2006 |
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LNCS 4141 |
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1 |
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804–815 |
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ADAS |
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ADAS @ adas @ JSL2006c |
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704 |
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Angel Sappa |
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Splitting up Panoramic Range Images into Compact 2½D Representations |
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2006 |
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International Journal of Imaging Systems and Technology, 16(3): 85–91 |
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ADAS |
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ADAS @ adas @ Sap2006b |
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721 |
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Angel Sappa; Boris X. Vintimilla |
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Edge Point Linking by Means of Global and Local Schemes |
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2006 |
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IEEE Int. Conf. on Signal-Image Technology and Internet-Based Systems, Hammamet, Tunisia, December 2006, pp. 551-560. |
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Hammamet (Tunisia) |
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ADAS |
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ADAS @ adas @ SaV2006 |
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722 |
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David Aldavert |
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Visual Simultaneous Localization and Mapping |
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2006 |
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CVC Technical Report #98 |
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CVC (UAB) |
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ADAS |
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Admin @ si @ Ald2006 |
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736 |
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David Geronimo |
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Model Features and Horizon Line Estimation for Pedestrian Detection in Advanced Driver Assistance Systems |
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2006 |
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CVC Technical Report #98 |
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CVC (UAB) |
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Master's thesis |
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ADAS |
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ADAS @ adas @ Ger2006 |
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737 |
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Author |
German Ros; J. Guerrero; Angel Sappa; Daniel Ponsa; Antonio Lopez |
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Title |
Fast and Robust l1-averaging-based Pose Estimation for Driving Scenarios |
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2013 |
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24th British Machine Vision Conference |
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SLAM |
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Robust visual pose estimation is at the core of many computer vision applications, being fundamental for Visual SLAM and Visual Odometry problems. During the last decades, many approaches have been proposed to solve these problems, being RANSAC one of the most accepted and used. However, with the arrival of new challenges, such as large driving scenarios for autonomous vehicles, along with the improvements in the data gathering frameworks, new issues must be considered. One of these issues is the capability of a technique to deal with very large amounts of data while meeting the realtime
constraint. With this purpose in mind, we present a novel technique for the problem of robust camera-pose estimation that is more suitable for dealing with large amount of data, which additionally, helps improving the results. The method is based on a combination of a very fast coarse-evaluation function and a robust ℓ1-averaging procedure. Such scheme leads to high-quality results while taking considerably less time than RANSAC.
Experimental results on the challenging KITTI Vision Benchmark Suite are provided, showing the validity of the proposed approach. |
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Bristol; UK; September 2013 |
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BMVC |
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Admin @ si @ RGS2013b; ADAS @ adas @ |
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2274 |
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