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Felipe Lumbreras; Ramon Baldrich; Maria Vanrell; Joan Serrat; Juan J. Villanueva |
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Title |
Multiresolution texture classification of ceramic tiles. |
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1999 |
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Recent Research developments in optical engineering, Research Signpost, 2: 213–228 |
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India |
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ADAS @ adas @ LBV1999b |
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45 |
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Author |
David Aldavert; Ricardo Toledo |
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Title |
Stereo Vision Local Map Alignment for Robot Environment Mapping |
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2008 |
Publication |
Robot Vision Second International Workshop, RobVis |
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4931 |
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111–124 |
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Auckland (New Zealand) |
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Admin @ si @ AlT2008 |
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1100 |
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Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez |
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Title |
Stereo Vision Camera Pose Estimation for On-Board Applications |
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Book Chapter |
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2007 |
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Scene Reconstruction, Pose Estimation and Traking |
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39-50 |
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Rustam Stolking |
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978-3-902613-06-6 |
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ADAS @ adas @ SGD2007 |
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797 |
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Author |
Cristhian Aguilera; M.Ramos; Angel Sappa |
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Title |
Simulated Annealing: A Novel Application of Image Processing in the Wood Area |
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2012 |
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Simulated Annealing – Advances, Applications and Hybridizations |
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91-104 |
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Marcos de Sales Guerra Tsuzuki |
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978-953-51-0710-1 |
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ADAS |
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Admin @ si @ ARS2012 |
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2156 |
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Author |
David Geronimo; Antonio Lopez |
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Title |
Vision-based Pedestrian Protection Systems for Intelligent Vehicles |
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2014 |
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SpringerBriefs in Computer Science |
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1-114 |
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Computer Vision; Driver Assistance Systems; Intelligent Vehicles; Pedestrian Detection; Vulnerable Road Users |
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Pedestrian Protection Systems (PPSs) are on-board systems aimed at detecting and tracking people in the surroundings of a vehicle in order to avoid potentially dangerous situations. These systems, together with other Advanced Driver Assistance Systems (ADAS) such as lane departure warning or adaptive cruise control, are one of the most promising ways to improve traffic safety. By the use of computer vision, cameras working either in the visible or infra-red spectra have been demonstrated as a reliable sensor to perform this task. Nevertheless, the variability of human’s appearance, not only in terms of clothing and sizes but also as a result of their dynamic shape, makes pedestrians one of the most complex classes even for computer vision. Moreover, the unstructured changing and unpredictable environment in which such on-board systems must work makes detection a difficult task to be carried out with the demanded robustness. In this brief, the state of the art in PPSs is introduced through the review of the most relevant papers of the last decade. A common computational architecture is presented as a framework to organize each method according to its main contribution. More than 300 papers are referenced, most of them addressing pedestrian detection and others corresponding to the descriptors (features), pedestrian models, and learning machines used. In addition, an overview of topics such as real-time aspects, systems benchmarking and future challenges of this research area are presented. |
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Springer Briefs in Computer Vision |
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978-1-4614-7986-4 |
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ADAS; 600.076 |
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GeL2014 |
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2325 |
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Author |
Hanne Kause; Aura Hernandez-Sabate; Patricia Marquez; Andrea Fuster; Luc Florack; Hans van Assen; Debora Gil |
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Title |
Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging |
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Book Chapter |
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2015 |
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Statistical Atlases and Computational Models of the Heart. Revised selected papers of Imaging and Modelling Challenges 6th International Workshop, STACOM 2015, Held in Conjunction with MICCAI 2015 |
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9534 |
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69-79 |
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Cardiac deformation and changes therein have been linked to pathologies. Both can be extracted in detail from tagged Magnetic Resonance Imaging (tMRI) using harmonic phase (HARP) images. Although point tracking algorithms have shown to have high accuracies on HARP images, these vary with position. Detecting and discarding areas with unreliable results is crucial for use in clinical support systems. This paper assesses the capability of two confidence measures (CMs), based on energy and image structure, for detecting locations with reduced accuracy in motion tracking results. These CMs were tested on a database of simulated tMRI images containing the most common artifacts that may affect tracking accuracy. CM performance is assessed based on its capability for HARP tracking error bounding and compared in terms of significant differences detected using a multi comparison analysis of variance that takes into account the most influential factors on HARP tracking performance. Results showed that the CM based on image structure was better suited to detect unreliable optical flow vectors. In addition, it was shown that CMs can be used to detect optical flow vectors with large errors in order to improve the optical flow obtained with the HARP tracking algorithm. |
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Munich; Germany; January 2015 |
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Springer International Publishing |
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0302-9743 |
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978-3-319-28711-9 |
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STACOM |
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ADAS; IAM; 600.075; 600.076; 600.060; 601.145 |
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Admin @ si @ KHM2015 |
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2734 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Real Time Image Registration for Planar Structure and 3D Sensor Pose Estimation |
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Book Chapter |
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2008 |
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Stereo Vision |
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18 |
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299–316 |
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Asim Bhatti |
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ADAS @ adas @ DoS2008c |
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1057 |
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Author |
Antonio Lopez |
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Title |
Pedestrian Detection Systems |
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2018 |
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Wiley Encyclopedia of Electrical and Electronics Engineering |
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Pedestrian detection is a highly relevant topic for both advanced driver assistance systems (ADAS) and autonomous driving. In this entry, we review the ideas behind pedestrian detection systems from the point of view of perception based on computer vision and machine learning. |
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ADAS; 600.118 |
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Admin @ si @ Lop2018 |
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3230 |
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