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Author |
Joan Serrat; Ferran Diego; Jose Manuel Alvarez; Felipe Lumbreras |
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Title |
Alignment of Videos Recorded from Moving Vehicles |
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Conference Article |
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2007 |
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in 14th International Conference on Image Analysis and Processing, |
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512–517 |
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Modena (Italia) |
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Call Number ![sorted by Call Number field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
ADAS @ adas @ SDA2007 |
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879 |
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Author |
Angel Sappa; Fadi Dornaika; David Geronimo; Antonio Lopez |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Efficient On-Board Stereo Vision Pose Estimation |
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Conference Article |
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Year |
2007 |
Publication |
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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Call Number ![sorted by Call Number field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
ADAS @ adas @ SDG2007b |
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916 |
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Author |
Angel Sappa; Fadi Dornaika; David Geronimo; Antonio Lopez |
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Title |
Registration-based Moving Object Detection from a Moving Camera |
Type |
Conference Article |
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Year |
2008 |
Publication |
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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Call Number ![sorted by Call Number field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
ADAS @ adas @ SDG2008 |
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1017 |
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Author |
Joan Serrat; Ferran Diego; Felipe Lumbreras; Jose Manuel Alvarez |
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Title |
Synchronization of Video Sequences from Free-moving Cameras |
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Conference Article |
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2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis |
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4477 |
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620–627 |
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Girona (Spain) |
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J. Marti et al. |
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IbPRIA |
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Call Number ![sorted by Call Number field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
ADAS @ adas @ SDL2007 |
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880 |
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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 |
Type |
Conference Article |
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Year |
2006 |
Publication |
International Conference on Image Analysis and Recognition |
Abbreviated Journal |
ICIAR |
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LNCS 4142 |
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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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Call Number ![sorted by Call Number field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
ADAS @ adas @ SGD2006b |
Serial |
671 |
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Author |
Angel Sappa; Rosa Herrero; Fadi Dornaika; David Geronimo; Antonio Lopez |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Road Approximation in Euclidean and v-Disparity Space: A Comparative Study |
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Conference Article |
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2007 |
Publication |
EUROCAST2007, Workshop on Cybercars and Intelligent Vehicles |
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368–369 |
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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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Las Palmas de Gran Canaria (Spain) |
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Call Number ![sorted by Call Number field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
ADAS @ adas @ SHD2007a |
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936 |
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Author |
Angel Sappa; Rosa Herrero; Fadi Dornaika; David Geronimo; Antonio Lopez |
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Title |
Road Approximation in Euclidean and v-Disparity Space: A Comparative Study |
Type |
Conference Article |
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Year |
2007 |
Publication |
Computer Aided Systems Theory, |
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4739 |
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1105–1112 |
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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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Las Palmas de Gran Canaria (Spain) |
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EUROCAST |
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ADAS |
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Call Number ![sorted by Call Number field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
ADAS @ adas @ SHD2007b |
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917 |
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Author |
Joan Serrat; Antonio Lopez; David Lloret |
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On ridges and valleys. |
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Conference Article |
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2000 |
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15 th International Conference on Pattern Recognition |
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4 |
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59-66 |
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Barcelona |
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ICPR |
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Call Number ![sorted by Call Number field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
ADAS @ adas @ SLL2000 d |
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334 |
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Author |
Yainuvis Socarras; David Vazquez; Antonio Lopez; David Geronimo; Theo Gevers |
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Title |
Improving HOG with Image Segmentation: Application to Human Detection |
Type |
Conference Article |
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Year |
2012 |
Publication |
11th International Conference on Advanced Concepts for Intelligent Vision Systems |
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7517 |
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178-189 |
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Keywords |
Segmentation; Pedestrian Detection |
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Abstract |
In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descriptor information and (ii) take advantage of the information of image segmentation, which in fact is likely to be used in other stages of the detection system such as candidate generation or refinement.
We test our technique in the INRIA person dataset, which was originally developed to test HOG, embedding it in a human detection system. The well-known segmentation method, mean-shift (from smaller to larger super-pixels), and different methods to re-weight the original descriptor (constant, region-luminance, color or texture-dependent) has been evaluated. We achieve performance improvements of 4:47% in detection rate through the use of differences of color between contour pixel neighborhoods as re-weighting function. |
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Brno, Czech Republic |
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Springer Berlin Heidelberg |
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J. Blanc-Talon et al. |
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English |
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0302-9743 |
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978-3-642-33139-8 |
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ACIVS |
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ADAS;ISE |
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Call Number ![sorted by Call Number field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
ADAS @ adas @ SLV2012 |
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1980 |
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Author |
Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Adapting Pedestrian Detection from Synthetic to Far Infrared Images |
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Conference Article |
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2013 |
Publication |
ICCV Workshop on Visual Domain Adaptation and Dataset Bias |
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Domain Adaptation; Far Infrared; Pedestrian Detection |
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We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes. |
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Sydney; Australia; December 2013 |
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Sydney, Australy |
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English |
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ICCVW-VisDA |
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ADAS; 600.054; 600.055; 600.057; 601.217;ISE |
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Call Number ![sorted by Call Number field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
ADAS @ adas @ SRV2013 |
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2334 |
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