toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Antonio Lopez; Joan Serrat; Cristina Cañero; Felipe Lumbreras edit   pdf
openurl 
  Title Robust Lane Lines Detection and Quantitative Assessment Type Conference Article
  Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 4477 Issue Pages 274–281  
  Keywords lane markings  
  Abstract  
  Address Girona (Spain)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor J. Marti et al  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference IbPRIA  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ LSC2007 Serial 881  
Permanent link to this record
 

 
Author David Lloret; Joan Serrat; Antonio Lopez; A. Soler; Juan J. Villanueva edit   pdf
openurl 
  Title Retinal image registration using creases as anatomical landmarks. Type Conference Article
  Year 2000 Publication 15 th International Conference on Pattern Recognition Abbreviated Journal  
  Volume 3 Issue Pages 207-2010  
  Keywords  
  Abstract Retinal images are routinely used in ophthalmology to study the optical nerve head and the retina. To assess objectively the evolution of an illness, images taken at different times must be registered. Most methods so far have been designed specifically for a single image modality, like temporal series or stereo pairs of angiographies, fluorescein angiographies or scanning laser ophthalmoscope (SLO) images, which makes them prone to fail when conditions vary. In contrast, the method we propose has shown to be accurate and reliable on all the former modalities. It has been adapted from the 3D registration of CT and MR image to 2D. Relevant features (also known as landmarks) are extracted by means of a robust creaseness operator, and resulting images are iteratively transformed until a maximum in their correlation is achieved. Our method has succeeded in more than 100 pairs tried so far, in all cases including also the scaling as a parameter to be optimized  
  Address Barcelona.  
  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 ICPR  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ LSL2000 c Serial 233  
Permanent link to this record
 

 
Author Judit Martinez; Eva Costa; P. Herreros; Antonio Lopez; Juan J. Villanueva edit  doi
openurl 
  Title TV-Screen Quality Inspection by Artificial Vision Type Conference Article
  Year 2003 Publication Proceedings SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision (QCAV 2003) Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract 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.  
  Address Gatlinburg, (EEUU)  
  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  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ MCH2003a Serial 393  
Permanent link to this record
 

 
Author Javier Marin; David Vazquez; David Geronimo; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Learning Appearance in Virtual Scenarios for Pedestrian Detection Type Conference Article
  Year 2010 Publication 23rd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 137–144  
  Keywords Pedestrian Detection; Domain Adaptation  
  Abstract Detecting pedestrians in images is a key functionality to avoid vehicle-to-pedestrian collisions. The most promising detectors rely on appearance-based pedestrian classifiers trained with labelled samples. This paper addresses the following question: can a pedestrian appearance model learnt in virtual scenarios work successfully for pedestrian detection in real images? (Fig. 1). Our experiments suggest a positive answer, which is a new and relevant conclusion for research in pedestrian detection. More specifically, we record training sequences in virtual scenarios and then appearance-based pedestrian classifiers are learnt using HOG and linear SVM. We test such classifiers in a publicly available dataset provided by Daimler AG for pedestrian detection benchmarking. This dataset contains real world images acquired from a moving car. The obtained result is compared with the one given by a classifier learnt using samples coming from real images. The comparison reveals that, although virtual samples were not specially selected, both virtual and real based training give rise to classifiers of similar performance.  
  Address San Francisco; CA; USA; June 2010  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language English Original Title Learning Appearance in Virtual Scenarios for Pedestrian Detection  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1063-6919 ISBN 978-1-4244-6984-0 Medium  
  Area Expedition Conference CVPR  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ MVG2010 Serial 1304  
Permanent link to this record
 

 
Author Javier Marin; David Vazquez; Antonio Lopez; Jaume Amores; Bastian Leibe edit   pdf
doi  openurl
  Title Random Forests of Local Experts for Pedestrian Detection Type Conference Article
  Year 2013 Publication 15th IEEE International Conference on Computer Vision Abbreviated Journal  
  Volume Issue Pages 2592 - 2599  
  Keywords ADAS; Random Forest; Pedestrian Detection  
  Abstract Pedestrian detection is one of the most challenging tasks in computer vision, and has received a lot of attention in the last years. Recently, some authors have shown the advantages of using combinations of part/patch-based detectors in order to cope with the large variability of poses and the existence of partial occlusions. In this paper, we propose a pedestrian detection method that efficiently combines multiple local experts by means of a Random Forest ensemble. The proposed method works with rich block-based representations such as HOG and LBP, in such a way that the same features are reused by the multiple local experts, so that no extra computational cost is needed with respect to a holistic method. Furthermore, we demonstrate how to integrate the proposed approach with a cascaded architecture in order to achieve not only high accuracy but also an acceptable efficiency. In particular, the resulting detector operates at five frames per second using a laptop machine. We tested the proposed method with well-known challenging datasets such as Caltech, ETH, Daimler, and INRIA. The method proposed in this work consistently ranks among the top performers in all the datasets, being either the best method or having a small difference with the best one.  
  Address Sydney; Australia; December 2013  
  Corporate Author Thesis  
  Publisher IEEE Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1550-5499 ISBN Medium  
  Area Expedition Conference ICCV  
  Notes ADAS; 600.057; 600.054 Approved no  
  Call Number (up) ADAS @ adas @ MVL2013 Serial 2333  
Permanent link to this record
 

 
Author R. de Nijs; Sebastian Ramos; Gemma Roig; Xavier Boix; Luc Van Gool; K. Kühnlenz. edit   pdf
openurl 
  Title On-line Semantic Perception Using Uncertainty Type Conference Article
  Year 2012 Publication International Conference on Intelligent Robots and Systems Abbreviated Journal IROS  
  Volume Issue Pages 4185-4191  
  Keywords Semantic Segmentation  
  Abstract Visual perception capabilities are still highly unreliable in unconstrained settings, and solutions might not beaccurate in all regions of an image. Awareness of the uncertainty of perception is a fundamental requirement for proper high level decision making in a robotic system. Yet, the uncertainty measure is often sacrificed to account for dependencies between object/region classifiers. This is the case of Conditional Random Fields (CRFs), the success of which stems from their ability to infer the most likely world configuration, but they do not directly allow to estimate the uncertainty of the solution. In this paper, we consider the setting of assigning semantic labels to the pixels of an image sequence. Instead of using a CRF, we employ a Perturb-and-MAP Random Field, a recently introduced probabilistic model that allows performing fast approximate sampling from its probability density function. This allows to effectively compute the uncertainty of the solution, indicating the reliability of the most likely labeling in each region of the image. We report results on the CamVid dataset, a standard benchmark for semantic labeling of urban image sequences. In our experiments, we show the benefits of exploiting the uncertainty by putting more computational effort on the regions of the image that are less reliable, and use more efficient techniques for other regions, showing little decrease of performance  
  Address  
  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 IROS  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ NRR2012 Serial 2378  
Permanent link to this record
 

 
Author Naveen Onkarappa; Angel Sappa edit  doi
isbn  openurl
  Title On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow Type Conference Article
  Year 2010 Publication 7th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 6111 Issue Pages 230-239  
  Keywords  
  Abstract This paper presents a robust technique for estimating on-board monocular vision system pose. The proposed approach is based on a dense optical flow that is robust against shadows, reflections and illumination changes. A RANSAC based scheme is used to cope with the outliers in the optical flow. The proposed technique is intended to be used in driver assistance systems for applications such as obstacle or pedestrian detection. Experimental results on different scenarios, both from synthetic and real sequences, shows usefulness of the proposed approach.  
  Address Povoa de Varzim (Portugal)  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-13771-6 Medium  
  Area Expedition Conference ICIAR  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ OnS2010 Serial 1342  
Permanent link to this record
 

 
Author A. Pujol; Felipe Lumbreras; Javier Varona; Juan J. Villanueva edit  openurl
  Title Locating people in indoor scenes for real applications. Type Conference Article
  Year 2000 Publication 15 th International Conference on Pattern Recognition Abbreviated Journal  
  Volume 4 Issue Pages 632-635  
  Keywords  
  Abstract  
  Address Barcelona.  
  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 ICPR  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ PLV2000 Serial 237  
Permanent link to this record
 

 
Author Daniel Ponsa; Antonio Lopez edit   pdf
openurl 
  Title Vehicle Trajectory Estimation based on Monocular Vision Type Conference Article
  Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 Abbreviated Journal  
  Volume Issue Pages 587-594  
  Keywords vehicle detection  
  Abstract  
  Address Girona (Spain)  
  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  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ PoL2007a Serial 785  
Permanent link to this record
 

 
Author Daniel Ponsa; Antonio Lopez edit   pdf
openurl 
  Title Feature Selection Based on a New Formulation of the Minimal-Redundancy-Maximal-Relevance Criterion Type Conference Article
  Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 Abbreviated Journal  
  Volume Issue Pages 47-54  
  Keywords  
  Abstract  
  Address Girona (Spain)  
  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  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ PoL2007b Serial 787  
Permanent link to this record
 

 
Author Daniel Ponsa; Antonio Lopez edit   pdf
openurl 
  Title Cascade of Classifiers for Vehicle Detection Type Conference Article
  Year 2007 Publication Advanced Concepts for Intelligent Vision Systems, LNCS 4678, volume 1, pp. 980–989 Abbreviated Journal  
  Volume Issue Pages  
  Keywords vehicle detection  
  Abstract  
  Address Delft (Netherlands)  
  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  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ PoL2007c Serial 935  
Permanent link to this record
 

 
Author Petia Radeva; Joan Serrat edit  openurl
  Title Rubber Snake: Implementation on Signed Distance Potential. Type Conference Article
  Year 1993 Publication Vision Conference Abbreviated Journal  
  Volume Issue Pages 187-194  
  Keywords  
  Abstract  
  Address Zurich, Switzerland.  
  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 SWISS  
  Notes ADAS;MILAB Approved no  
  Call Number (up) ADAS @ adas @ RaS1993 Serial 170  
Permanent link to this record
 

 
Author Gemma Roig; Xavier Boix; R. de Nijs; Sebastian Ramos; K. Kühnlenz; Luc Van Gool edit   pdf
doi  openurl
  Title Active MAP Inference in CRFs for Efficient Semantic Segmentation Type Conference Article
  Year 2013 Publication 15th IEEE International Conference on Computer Vision Abbreviated Journal  
  Volume Issue Pages 2312 - 2319  
  Keywords Semantic Segmentation  
  Abstract Most MAP inference algorithms for CRFs optimize an energy function knowing all the potentials. In this paper, we focus on CRFs where the computational cost of instantiating the potentials is orders of magnitude higher than MAP inference. This is often the case in semantic image segmentation, where most potentials are instantiated by slow classifiers fed with costly features. We introduce Active MAP inference 1) to on-the-fly select a subset of potentials to be instantiated in the energy function, leaving the rest of the parameters of the potentials unknown, and 2) to estimate the MAP labeling from such incomplete energy function. Results for semantic segmentation benchmarks, namely PASCAL VOC 2010 [5] and MSRC-21 [19], show that Active MAP inference achieves similar levels of accuracy but with major efficiency gains.  
  Address Sydney; Australia; December 2013  
  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 1550-5499 ISBN Medium  
  Area Expedition Conference ICCV  
  Notes ADAS; 600.057 Approved no  
  Call Number (up) ADAS @ adas @ RBN2013 Serial 2377  
Permanent link to this record
 

 
Author Mohammad Rouhani; Angel Sappa edit  doi
isbn  openurl
  Title A Novel Approach to Geometric Fitting of Implicit Quadrics Type Conference Article
  Year 2009 Publication 8th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal  
  Volume 5807 Issue Pages 121–132  
  Keywords  
  Abstract This paper presents a novel approach for estimating the geometric distance from a given point to the corresponding implicit quadric curve/surface. The proposed estimation is based on the height of a tetrahedron, which is used as a coarse but reliable estimation of the real distance. The estimated distance is then used for finding the best set of quadric parameters, by means of the Levenberg-Marquardt algorithm, which is a common framework in other geometric fitting approaches. Comparisons of the proposed approach with previous ones are provided to show both improvements in CPU time as well as in the accuracy of the obtained results.  
  Address Bordeaux, France  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-04696-4 Medium  
  Area Expedition Conference ACIVS  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ RoS2009 Serial 1194  
Permanent link to this record
 

 
Author Mohammad Rouhani; Angel Sappa edit  doi
isbn  openurl
  Title Relaxing the 3L Algorithm for an Accurate Implicit Polynomial Fitting Type Conference Article
  Year 2010 Publication 23rd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 3066-3072  
  Keywords  
  Abstract This paper presents a novel method to increase the accuracy of linear fitting of implicit polynomials. The proposed method is based on the 3L algorithm philosophy. The novelty lies on the relaxation of the additional constraints, already imposed by the 3L algorithm. Hence, the accuracy of the final solution is increased due to the proper adjustment of the expected values in the aforementioned additional constraints. Although iterative, the proposed approach solves the fitting problem within a linear framework, which is independent of the threshold tuning. Experimental results, both in 2D and 3D, showing improvements in the accuracy of the fitting are presented. Comparisons with both state of the art algorithms and a geometric based one (non-linear fitting), which is used as a ground truth, are provided.  
  Address San Francisco; CA; USA; June 2010  
  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 1063-6919 ISBN 978-1-4244-6984-0 Medium  
  Area Expedition Conference CVPR  
  Notes ADAS Approved no  
  Call Number (up) ADAS @ adas @ RoS2010a Serial 1303  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: