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Author |
Jaume Amores; Petia Radeva |
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Title |
Registration and retrieval of medical images. Application to IVUS |
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2004 |
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CVC Technical Report #77 |
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MILAB |
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ADAS @ adas @ AmR2004 |
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513 |
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Author |
David Geronimo |
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Title |
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 |
Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez |
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Title |
Stereo Matching using SGM on the GPU |
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2016 |
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Programming and Tuning Massively Parallel Systems |
Abbreviated Journal |
PUMPS |
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CUDA; Stereo; Autonomous Vehicle |
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Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy efficient GPU devices. Our design runs on a Tegra X1 at 42 frames per second (fps) for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method. |
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ADAS; 600.085; 600.087; 600.076 |
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ADAS @ adas @ HCE2016b |
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2776 |
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Author |
Antonio Lopez; Felipe Lumbreras; Joan Serrat |
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Title |
Efficient computation of local creaseness |
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1997 |
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CVC Technical Report |
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15 |
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CVC, Bellaterra (Spain) |
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ADAS |
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ADAS @ adas @ LLS1997b |
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527 |
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Author |
Antonio Lopez; Joan Serrat |
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Title |
Ridge/Valley-like structures: Creases, separatrices and drainage patterns |
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1997 |
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CVC Technical Report #21 |
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ADAS |
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ADAS @ adas @ LoS1997 |
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524 |
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Author |
Antonio Lopez; Joan Serrat |
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Title |
Ridges and Valleys in Image Analysis |
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1998 |
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CVC Technical Report #22 |
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ADAS |
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ADAS @ adas @ LoS1998 |
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533 |
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Author |
Felipe Lumbreras; Joan Serrat |
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Title |
Segmentation of petrographical image of marbles |
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1996 |
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CVC Technical Report #04 |
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ADAS |
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ADAS @ adas @ LuS1996c |
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93 |
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Author |
Felipe Lumbreras; Joan Serrat |
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Title |
Wavelet filtering for the segmentation of marble images |
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1996 |
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CVC Technical Report #05 |
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ADAS |
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ADAS @ adas @ LuS1996d |
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92 |
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Author |
Daniel Ponsa |
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Title |
A model based pedestrian tracking review |
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2001 |
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CVC Technical Report #69 |
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invisible;ADAS |
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ADAS @ adas @ Pon2001 |
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522 |
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Author |
David Vazquez; Enrique Cabello |
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Title |
Empleo de sistemas biométricos faciales aplicados al reconocimiento de personas en aeropuertos |
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Report |
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2007 |
Publication |
Ingeniería Técnica en Informática de Sistemas |
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Surveillance; Face detection; Face recognition |
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El presente proyecto se desarrolló a lo largo del año 2005 y 2006, probando un prototipo de un sistema de verificación facial con imágenes extraídas de las cámaras de video-vigilancia del aeropuerto de Barajas. Se diseñaron varios experimentos, agrupados en dos clases. En el primer tipo, el sistema es entre- nado con imágenes obtenidas en condiciones de laboratorio y luego probado con imágenes extraídas de las cámaras de video-vigilancia del aeropuerto de Barajas. En el segundo caso, tanto las imágenes de entrenamiento como las de prueba corresponden a imágenes extraídas de Barajas.
Se ha desarrollado un sistema completo, que incluye adquisición y digitalización de las imágenes, localización y recorte de las caras en escena, verificación de sujetos y obtención de resultados. Los resultados muestran que, en general, un sistema de verificación facial basado en imágenes puede ser una valiosa ayuda a un operario que deba estar vigilando amplias zonas. |
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Bachelor's thesis |
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invisible;ADAS |
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ADAS @ adas @ VC2007a |
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1671 |
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Author |
David Vazquez; David Geronimo; Antonio Lopez |
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Title |
The effect of the distance in pedestrian detection |
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2009 |
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CVC Technical Report |
Abbreviated Journal |
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149 |
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Pedestrian Detection |
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Abstract |
Pedestrian accidents are one of the leading preventable causes of death. In order to reduce the number of accidents, in the last decade the pedestrian protection systems have been introduced, a special type of advanced driver assistance systems, in witch an on-board camera explores the road ahead for possible collisions with pedestrians in order to warn the driver or perform braking actions. As a result of the variability of the appearance, pose and size, pedestrian detection is a very challenging task. So many techniques, models and features have been proposed to solve the problem. As the appearance of pedestrians varies signi cantly as a function of distance, a system based on multiple classi ers specialized on diferent depths is likely to improve the overall performance with respect to a typical system based on a general detector. Accordingly, the main aim of this work is to explore the e ect of the distance in pedestrian detection. We have evaluated three pedestrian detectors (HOG, HAAR and EOH) in two di erent databases (INRIA and Daimler09) for two di erent sizes (small and big). By a extensive set of experiments we answer to questions like which datasets and evaluation methods are the most adequate, which is the best method for each size of the pedestrians and why or how do the method optimum parameters vary with respect to the distance |
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M.Sc. |
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ADAS |
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ADAS @ adas @ VGL2009 |
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1669 |
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Author |
David Vazquez; Antonio Lopez |
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Title |
Intrusion Classification in Intelligent Video Surveillance Systems |
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2008 |
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Estudis d'Enginyeria Superior en Informática |
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UAB |
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Human detection; Car detection; Intrusion detection |
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An intelligent video surveillance system (IVS) is a camera-based installation able to process in real-time the images coming from the cameras. The aim is to automatically warn about different events of interest at the moment they happen. Daview system of Davantis is a com mercial example of IVS system. The problems addressed by any IVS system, and so Daview, are so challenging that none IVS system is perfect, thus, they need continuous improvement. Accordingly, this project aims to study different approaches in order to outperform current Daview performance, in particular, we bet for improving its classification core. We present an in deep study of the state of the art on IVS systems, as well as on how Daview works. Based on that knowledge, we propose four possibilities for improving Daview classification capabilities: improve existent classifiers; improve existing classifiers combination; create new classifiers and create new classifier-based architectures. Our main contribution has been the incorporation of state-of-the-art feature selection and machine learning techniques for the classification tasks, a viewpoint not fully addressed in current Daview system. After a comprehensive quantitative evaluation we will see how one of our proposals clearly outperforms the overall performance of current Daview system. In particular the classification core that we finally propose consists in an AdaBoost One-Against-All architecture that uses appearance and motion features that were already present in current Daview system |
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Bellaterra, Spain |
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PFC |
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ADAS |
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ADAS @ adas @ VL2008a |
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1670 |
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Author |
Oriol Martinez |
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Semantic Retrieval of Memory Color Content |
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2004 |
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CVC Technical Report #80 |
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Admin @ si @ 38047 |
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508 |
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Author |
Carme Julia |
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Motion segmentation through factorization. Application to night driving assistance |
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2004 |
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CVC Technical Report #79 |
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Admin @ si @ 38169 |
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506 |
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Author |
David Alcalde |
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Image classification in terms of rotation-invariant pattern matching |
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2003 |
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CVC Technical Report #73 |
Abbreviated Journal |
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Admin @ si @ Alc2003 |
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518 |
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