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| Author | Ferran Diego; Jose Manuel Alvarez; Joan Serrat; Antonio Lopez | ||||
| Title | Vision-based road detection via on-line video registration | Type | Conference Article | ||
| Year | 2010 | Publication | 13th Annual International Conference on Intelligent Transportation Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 1135–1140 | ||
| Keywords | video alignment; road detection | ||||
| Abstract | TB6.2
Road segmentation is an essential functionality for supporting advanced driver assistance systems (ADAS) such as road following and vehicle and pedestrian detection. Significant efforts have been made in order to solve this task using vision-based techniques. The major challenge is to deal with lighting variations and the presence of objects on the road surface. In this paper, we propose a new road detection method to infer the areas of the image depicting road surfaces without performing any image segmentation. The idea is to previously segment manually or semi-automatically the road region in a traffic-free reference video record on a first drive. And then to transfer these regions to the frames of a second video sequence acquired later in a second drive through the same road, in an on-line manner. This is possible because we are able to automatically align the two videos in time and space, that is, to synchronize them and warp each frame of the first video to its corresponding frame in the second one. The geometric transform can thus transfer the road region to the present frame on-line. In order to reduce the different lighting conditions which are present in outdoor scenarios, our approach incorporates a shadowless feature space which represents an image in an illuminant-invariant feature space. Furthermore, we propose a dynamic background subtraction algorithm which removes the regions containing vehicles in the observed frames which are within the transferred road region. |
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| Address | Madeira Island (Portugal) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2153-0009 | ISBN | 978-1-4244-7657-2 | Medium | |
| Area | Expedition | Conference | ITSC | ||
| Notes | ADAS | Approved | no | ||
Call Number  |
ADAS @ adas @ DAS2010 | Serial | 1424 | ||
| Permanent link to this record | |||||
| Author | Victor Campmany; Sergio Silva; Juan Carlos Moure; Toni Espinosa; David Vazquez; Antonio Lopez | ||||
| Title | GPU-based pedestrian detection for autonomous driving | Type | Conference Article | ||
| Year | 2016 | Publication | GPU Technology Conference | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Pedestrian Detection; GPU | ||||
| Abstract | Pedestrian detection for autonomous driving is one of the hardest tasks within computer vision, and involves huge computational costs. Obtaining acceptable real-time performance, measured in frames per second (fps), for the most advanced algorithms is nowadays a hard challenge. Taking the work in [1] as our baseline, we propose a CUDA implementation of a pedestrian detection system that includes LBP and HOG as feature descriptors and SVM and Random forest as classifiers. We introduce significant algorithmic adjustments and optimizations to adapt the problem to the NVIDIA GPU architecture. The aim is to deploy a real-time system providing reliable results. | ||||
| Address | Silicon Valley; San Francisco; USA; April 2016 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | GTC | ||
| Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
| Call Number |
ADAS @ adas @ CSM2016 | Serial | 2737 | ||
| Permanent link to this record | |||||
| Author | Victor Campmany; Sergio Silva; Juan Carlos Moure; Antoni Espinosa; David Vazquez; Antonio Lopez | ||||
| Title | GPU-based pedestrian detection for autonomous driving | Type | Abstract | ||
| Year | 2015 | Publication | Programming and Tunning Massive Parallel Systems | Abbreviated Journal | PUMPS |
| Volume | Issue | Pages | |||
| Keywords | Autonomous Driving; ADAS; CUDA; Pedestrian Detection | ||||
| Abstract | Pedestrian detection for autonomous driving has gained a lot of prominence during the last few years. Besides the fact that it is one of the hardest tasks within computer vision, it involves huge computational costs. The real-time constraints in the field are tight, and regular processors are not able to handle the workload obtaining an acceptable ratio of frames per second (fps). Moreover, multiple cameras are required to obtain accurate results, so the need to speed up the process is even higher. Taking the work in [1] as our baseline, we propose a CUDA implementation of a pedestrian detection system. Further, we introduce significant algorithmic adjustments and optimizations to adapt the problem to the GPU architecture. The aim is to provide a system capable of running in real-time obtaining reliable results. | ||||
| Address | Barcelona; Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | PUMPS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | PUMPS | ||
| Notes | ADAS; 600.076; 600.082; 600.085 | Approved | no | ||
| Call Number |
ADAS @ adas @ CSM2015 | Serial | 2644 | ||
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| Author | Victor Campmany; Sergio Silva; Antonio Espinosa; Juan Carlos Moure; David Vazquez; Antonio Lopez | ||||
| Title | GPU-based pedestrian detection for autonomous driving | Type | Conference Article | ||
| Year | 2016 | Publication | 16th International Conference on Computational Science | Abbreviated Journal | |
| Volume | 80 | Issue | Pages | 2377-2381 | |
| Keywords | Pedestrian detection; Autonomous Driving; CUDA | ||||
| Abstract | We propose a real-time pedestrian detection system for the embedded Nvidia Tegra X1 GPU-CPU hybrid platform. The pipeline is composed by the following state-of-the-art algorithms: Histogram of Local Binary Patterns (LBP) and Histograms of Oriented Gradients (HOG) features extracted from the input image; Pyramidal Sliding Window technique for foreground segmentation; and Support Vector Machine (SVM) for classification. Results show a 8x speedup in the target Tegra X1 platform and a better performance/watt ratio than desktop CUDA platforms in study. | ||||
| Address | San Diego; CA; USA; June 2016 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICCS | ||
| Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
| Call Number |
ADAS @ adas @ CSE2016 | Serial | 2741 | ||
| Permanent link to this record | |||||
| Author | Diego Alejandro Cheda; Daniel Ponsa; Antonio Lopez | ||||
| Title | Camera Egomotion Estimation in the ADAS Context | Type | Conference Article | ||
| Year | 2010 | Publication | 13th International IEEE Annual Conference on Intelligent Transportation Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 1415–1420 | ||
| Keywords | |||||
| Abstract | Camera-based Advanced Driver Assistance Systems (ADAS) have concentrated many research efforts in the last decades. Proposals based on monocular cameras require the knowledge of the camera pose with respect to the environment, in order to reach an efficient and robust performance. A common assumption in such systems is considering the road as planar, and the camera pose with respect to it as approximately known. However, in real situations, the camera pose varies along time due to the vehicle movement, the road slope, and irregularities on the road surface. Thus, the changes in the camera position and orientation (i.e., the egomotion) are critical information that must be estimated at every frame to avoid poor performances. This work focuses on egomotion estimation from a monocular camera under the ADAS context. We review and compare egomotion methods with simulated and real ADAS-like sequences. Basing on the results of our experiments, we show which of the considered nonlinear and linear algorithms have the best performance in this domain. | ||||
| Address | Madeira Island (Portugal) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2153-0009 | ISBN | 978-1-4244-7657-2 | Medium | |
| Area | Expedition | Conference | ITSC | ||
| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ CPL2010 | Serial | 1425 | ||
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| Author | Enrique Cabello; Cristina Conde; Angel Serrano; Licesio Rodriguez; David Vazquez | ||||
| Title | Empleo de sistemas biométricos para el reconocimiento de personas en aeropuertos | Type | Journal Article | ||
| Year | 2006 | Publication | Instituto Universitario de Investigación sobre Seguridad Interior (IUSI 2006) | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Surveillance; Face detection; Face recognition | ||||
| Abstract | El presente proyecto se desarrolló a lo largo del año 2005, 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 entrenado 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 ayuda a un operario que deba estar vigilando amplias zonas. | ||||
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| Area | Expedition | Conference | |||
| Notes | invisible;ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ CCS2006a | Serial | 1672 | ||
| Permanent link to this record | |||||
| Author | Hugo Berti; Angel Sappa; Osvaldo Agamennoni | ||||
| Title | Improved Dynamic Window Approach by Using Lyapunov Stability Criteria | Type | Journal | ||
| Year | 2008 | Publication | Latin American Applied Research | Abbreviated Journal | |
| Volume | 38 | Issue | 4 | Pages | 289–298 |
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| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ BSA2008 | Serial | 1056 | ||
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| Author | Hugo Berti; Angel Sappa; Osvaldo Agamennoni | ||||
| Title | Autonomous robot navigation with a global and asymptotic convergence | Type | Conference Article | ||
| Year | 2007 | Publication | IEEE International Conference on Robotics and Automation | Abbreviated Journal | |
| Volume | Issue | Pages | 2712–2717 | ||
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| Address | Roma (Italy) | ||||
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| Area | Expedition | Conference | ICRA | ||
| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ BSA2007 | Serial | 796 | ||
| Permanent link to this record | |||||
| Author | Fernando Barrera; Felipe Lumbreras; Angel Sappa | ||||
| Title | Multimodal Template Matching based on Gradient and Mutual Information using Scale-Space | Type | Conference Article | ||
| Year | 2010 | Publication | 17th IEEE International Conference on Image Processing | Abbreviated Journal | |
| Volume | Issue | Pages | 2749–2752 | ||
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| Abstract | This paper presents the combined use of gradient and mutual information for infrared and intensity templates matching. We propose to joint: (i) feature matching in a multiresolution context and (ii) information propagation through scale-space representations. Our method consists in combining mutual information with a shape descriptor based on gradient, and propagate them following a coarse-to-fine strategy. The main contributions of this work are: to offer a theoretical formulation towards a multimodal stereo matching; to show that gradient and mutual information can be reinforced while they are propagated between consecutive levels; and to show that they are valid cost functions in multimodal template matchings. Comparisons are presented showing the improvements and viability of the proposed approach. | ||||
| Address | Hong-Kong | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1522-4880 | ISBN | 978-1-4244-7992-4 | Medium | |
| Area | Expedition | Conference | ICIP | ||
| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ BLS2010 | Serial | 1358 | ||
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| Author | Xavier Boix; Josep M. Gonfaus; Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Marco Pedersoli; Jordi Gonzalez; Joan Serrat | ||||
| Title | Combining local and global bag-of-word representations for semantic segmentation | Type | Conference Article | ||
| Year | 2009 | Publication | Workshop on The PASCAL Visual Object Classes Challenge | Abbreviated Journal | |
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| Address | Kyoto (Japan) | ||||
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| Area | Expedition | Conference | ICCV | ||
| Notes | ADAS;ISE | Approved | no | ||
| Call Number |
ADAS @ adas @ BGS2009 | Serial | 1273 | ||
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| Author | Jorge Bernal; David Vazquez (eds) | ||||
| Title | Computer vision Trends and Challenges | Type | Book Whole | ||
| Year | 2013 | Publication | Computer vision Trends and Challenges | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | CVCRD; Computer Vision | ||||
| Abstract | This book contains the papers presented at the Eighth CVC Workshop on Computer Vision Trends and Challenges (CVCR&D'2013). The workshop was held at the Computer Vision Center (Universitat Autònoma de Barcelona), the October 25th, 2013. The CVC workshops provide an excellent opportunity for young researchers and project engineers to share new ideas and knowledge about the progress of their work, and also, to discuss about challenges and future perspectives. In addition, the workshop is the welcome event for new people that recently have joined the institute.
The program of CVCR&D is organized in a single-track single-day workshop. It comprises several sessions dedicated to specific topics. For each session, a doctor working on the topic introduces the general research lines. The PhD students expose their specific research. A poster session will be held for open questions. Session topics cover the current research lines and development projects of the CVC: Medical Imaging, Medical Imaging, Color & Texture Analysis, Object Recognition, Image Sequence Evaluation, Advanced Driver Assistance Systems, Machine Vision, Document Analysis, Pattern Recognition and Applications. We want to thank all paper authors and Program Committee members. Their contribution shows that the CVC has a dynamic, active, and promising scientific community. We hope you all enjoy this Eighth workshop and we are looking forward to meeting you and new people next year in the Ninth CVCR&D. |
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| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | Jorge Bernal; David Vazquez | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-940902-2-6 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number |
ADAS @ adas @ BeV2013 | Serial | 2339 | ||
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| Author | Jaume Amores; N. Sebe; Petia Radeva | ||||
| Title | Context-Based Object-Class Recognition and Retrieval by Generalized Correlograms | Type | Journal | ||
| Year | 2007 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29(10):1818–1833, (ISI 3,81) | Abbreviated Journal | |
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| Notes | ADAS;MILAB | Approved | no | ||
| Call Number |
ADAS @ adas @ ASR2007b | Serial | 922 | ||
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| Author | Jaume Amores; N. Sebe; Petia Radeva | ||||
| Title | Class-Specific Binaryy Correlograms for Object Recognition | Type | Conference Article | ||
| Year | 2007 | Publication | British Machine Vision Conference | Abbreviated Journal | |
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| Address | Warwick (UK) | ||||
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| Area | Expedition | Conference | BMVC’07 | ||
| Notes | ADAS;MILAB | Approved | no | ||
| Call Number |
ADAS @ adas @ ASR2007a | Serial | 923 | ||
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| Author | Jaume Amores; N. Sebe; Petia Radeva | ||||
| Title | Boosting the distance estimation: Application to the K-Nearest Neighbor Classifier | Type | Journal Article | ||
| Year | 2006 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 27 | Issue | 3 | Pages | 201–209 |
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| Notes | ADAS;MILAB | Approved | no | ||
| Call Number |
ADAS @ adas @ ASR2006 | Serial | 643 | ||
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| Author | Jaume Amores; N. Sebe; Petia Radeva | ||||
| Title | Efficient Object-Class Recognition by Boosting Contextual Information | Type | Miscellaneous | ||
| Year | 2005 | Publication | Pattern Recognition and Image Analysis, IbPRIA 2005, LNCS 3522:28–35 | Abbreviated Journal | |
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| Address | Estoril (Portugal) | ||||
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| Notes | ADAS;MILAB | Approved | no | ||
| Call Number |
ADAS @ adas @ ASR2005b | Serial | 554 | ||
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