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Author |
A. Pujol; Felipe Lumbreras; Javier Varona; Juan J. Villanueva |
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Locating people in indoor scenes for real applications. |
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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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632-635 |
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Barcelona. |
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ADAS @ adas @ PLV2000 |
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237 |
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Author |
M.J. Yzuel; J. Pladellorens; Joan Serrat; A. Dupuy |
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Title |
Application restauration and edge detection techniques in the calculation of left ventricular volumes. |
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1993 |
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Optics in Medicine, Biology and Environmental Research : Selected contributions to the first International Conference on Optics within Life Sciences (OWLS I) |
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374-375 |
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Elsevier |
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ADAS @ adas @ YPS1993 |
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244 |
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Author |
Joan Serrat; J. Argemi; Juan J. Villanueva |
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Title |
Automatization of TW2 method using a knowledge-based image analysis system. |
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1991 |
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VIth International Congress of Auxology. |
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Madrid |
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ADAS @ adas @ SAV1991 |
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259 |
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Author |
Joan Serrat; Antonio Lopez; David Lloret |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
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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ADAS @ adas @ SLL2000 d |
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334 |
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Author |
Judit Martinez; Eva Costa; P. Herreros; Antonio Lopez; Juan J. Villanueva |
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Title |
TV-Screen Quality Inspection by Artificial Vision |
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Conference Article |
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2003 |
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Proceedings SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision (QCAV 2003) |
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A real-time vision system for TV screen quality inspection is introduced. The whole system consists of eight cameras and one processor per camera. It acquires and processes 112 images in 6 seconds. The defects to be inspected can be grouped into four main categories (bubble, line-out, line reduction and landing) although there exists a large variability among each particular type of defect. The complexity of the whole inspection process has been reduced by dividing images into smaller ones and grouping the defects into frequency and intensity relevant ones. Tools such as mathematical morphology, Fourier transform, profile analysis and classification have been used. The performance of the system has been successfully proved against human operators in normal production conditions. |
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Gatlinburg, (EEUU) |
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ADAS @ adas @ MCH2003a |
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393 |
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Author |
Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis |
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Title |
Monocular 3D Human Body Reconstruction Towards Depth Augmentation of Television Sequences |
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Conference Article |
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2003 |
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IEEE International Conference on Image Processing, Barcelona, Spain, September 2003 |
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325-328 |
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Barcelona |
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ADAS @ adas @ SAM2003 |
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418 |
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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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Year |
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 |
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459 |
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Author |
Muhammad Anwer Rao; David Vazquez; Antonio Lopez |
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Title |
Opponent Colors for Human Detection |
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Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
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6669 |
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363-370 |
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Pedestrian Detection; Color; Part Based Models |
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Abstract |
Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper. |
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Las Palmas de Gran Canaria. Spain |
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Springer |
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Berlin Heidelberg |
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J. Vitria; J.M. Sanches; M. Hernandez |
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English |
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English |
Original Title |
Opponent Colors for Human Detection |
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Lecture Notes on Computer Science |
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LNCS |
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0302-9743 |
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978-3-642-21256-7 |
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IbPRIA |
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ADAS @ adas @ RVL2011a |
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1666 |
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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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Year |
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; 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 |
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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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ADAS @ adas @ SGD2006b |
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671 |
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