toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
  Records Links
Author Joan Serrat; Ferran Diego; Felipe Lumbreras; Jose Manuel Alvarez edit  openurl
  Title Synchronization of Video Sequences from Free-moving Cameras Type Conference Article
  Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 4477 Issue Pages (down) 620–627  
  Keywords  
  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 ADAS @ adas @ SDL2007 Serial 880  
Permanent link to this record
 

 
Author Mohammad Rouhani; E. Boyer; Angel Sappa edit   pdf
doi  openurl
  Title Non-Rigid Registration meets Surface Reconstruction Type Conference Article
  Year 2014 Publication International Conference on 3D Vision Abbreviated Journal  
  Volume Issue Pages (down) 617-624  
  Keywords  
  Abstract Non rigid registration is an important task in computer vision with many applications in shape and motion modeling. A fundamental step of the registration is the data association between the source and the target sets. Such association proves difficult in practice, due to the discrete nature of the information and its corruption by various types of noise, e.g. outliers and missing data. In this paper we investigate the benefit of the implicit representations for the non-rigid registration of 3D point clouds. First, the target points are described with small quadratic patches that are blended through partition of unity weighting. Then, the discrete association between the source and the target can be replaced by a continuous distance field induced by the interface. By combining this distance field with a proper deformation term, the registration energy can be expressed in a linear least square form that is easy and fast to solve. This significantly eases the registration by avoiding direct association between points. Moreover, a hierarchical approach can be easily implemented by employing coarse-to-fine representations. Experimental results are provided for point clouds from multi-view data sets. The qualitative and quantitative comparisons show the outperformance and robustness of our framework. %in presence of noise and outliers.  
  Address Tokyo; Japan; December 2014  
  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 3DV  
  Notes ADAS; 600.055; 600.076 Approved no  
  Call Number Admin @ si @ RBS2014 Serial 2534  
Permanent link to this record
 

 
Author Naveen Onkarappa; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa edit   pdf
doi  openurl
  Title Cross-spectral Stereo Correspondence using Dense Flow Fields Type Conference Article
  Year 2014 Publication 9th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 3 Issue Pages (down) 613-617  
  Keywords Cross-spectral Stereo Correspondence; Dense Optical Flow; Infrared and Visible Spectrum  
  Abstract This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing the validity of the proposed approach.  
  Address Lisboa; Portugal; January 2014  
  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 VISAPP  
  Notes ADAS; 600.055; 600.076 Approved no  
  Call Number Admin @ si @ OAV2014 Serial 2477  
Permanent link to this record
 

 
Author Jose Manuel Alvarez; Theo Gevers; Antonio Lopez edit  url
doi  openurl
  Title Evaluating Color Representation for Online Road Detection Type Conference Article
  Year 2013 Publication ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars Abbreviated Journal  
  Volume Issue Pages (down) 594-595  
  Keywords  
  Abstract Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired
using an on-board camera in different real-driving situations.
 
  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 CVVT:E2M  
  Notes ADAS;ISE Approved no  
  Call Number Admin @ si @ AGL2013 Serial 2794  
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 (down) 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 ADAS @ adas @ PoL2007a Serial 785  
Permanent link to this record
 

 
Author Jose Manuel Alvarez; Y. LeCun; Theo Gevers; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Semantic Road Segmentation via Multi-Scale Ensembles of Learned Features Type Conference Article
  Year 2012 Publication 12th European Conference on Computer Vision – Workshops and Demonstrations Abbreviated Journal  
  Volume 7584 Issue Pages (down) 586-595  
  Keywords road detection  
  Abstract Semantic segmentation refers to the process of assigning an object label (e.g., building, road, sidewalk, car, pedestrian) to every pixel in an image. Common approaches formulate the task as a random field labeling problem modeling the interactions between labels by combining local and contextual features such as color, depth, edges, SIFT or HoG. These models are trained to maximize the likelihood of the correct classification given a training set. However, these approaches rely on hand–designed features (e.g., texture, SIFT or HoG) and a higher computational time required in the inference process.
Therefore, in this paper, we focus on estimating the unary potentials of a conditional random field via ensembles of learned features. We propose an algorithm based on convolutional neural networks to learn local features from training data at different scales and resolutions. Then, diversification between these features is exploited using a weighted linear combination. Experiments on a publicly available database show the effectiveness of the proposed method to perform semantic road scene segmentation in still images. The algorithm outperforms appearance based methods and its performance is similar compared to state–of–the–art methods using other sources of information such as depth, motion or stereo.
 
  Address  
  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 978-3-642-33867-0 Medium  
  Area Expedition Conference ECCVW  
  Notes ADAS;ISE Approved no  
  Call Number Admin @ si @ ALG2012; ADAS @ adas Serial 2187  
Permanent link to this record
 

 
Author Jose Manuel Alvarez; Theo Gevers; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Learning Photometric Invariance from Diversified Color Model Ensembles Type Conference Article
  Year 2009 Publication 22nd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages (down) 565–572  
  Keywords road detection  
  Abstract Color is a powerful visual cue for many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the imaging conditions affecting negatively the performance of the task at hand. Often, a reflection model (e.g., Lambertian or dichromatic reflectance) is used to derive color invariant models. However, those reflection models might be too restricted to model real-world scenes in which different reflectance mechanisms may hold simultaneously. Therefore, in this paper, we aim to derive color invariance by learning from color models to obtain diversified color invariant ensembles. First, a photometrical orthogonal and non-redundant color model set is taken on input composed of both color variants and invariants. Then, the proposed method combines and weights these color models to arrive at a diversified color ensemble yielding a proper balance between invariance (repeatability) and discriminative power (distinctiveness). To achieve this, the fusion method uses a multi-view approach to minimize the estimation error. In this way, the method is robust to data uncertainty and produces properly diversified color invariant ensembles. Experiments are conducted on three different image datasets to validate the method. From the theoretical and experimental results, it is concluded that the method is robust against severe variations in imaging conditions. The method is not restricted to a certain reflection model or parameter tuning. Further, the method outperforms state-of- the-art detection techniques in the field of object, skin and road recognition.  
  Address Miami (USA)  
  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 978-1-4244-3992-8 Medium  
  Area Expedition Conference CVPR  
  Notes ADAS;ISE Approved no  
  Call Number ADAS @ adas @ AGL2009 Serial 1169  
Permanent link to this record
 

 
Author Alejandro Gonzalez Alzate; Gabriel Villalonga; German Ros; David Vazquez; Antonio Lopez edit   pdf
doi  openurl
  Title 3D-Guided Multiscale Sliding Window for Pedestrian Detection Type Conference Article
  Year 2015 Publication Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 Abbreviated Journal  
  Volume 9117 Issue Pages (down) 560-568  
  Keywords Pedestrian Detection  
  Abstract The most relevant modules of a pedestrian detector are the candidate generation and the candidate classification. The former aims at presenting image windows to the latter so that they are classified as containing a pedestrian or not. Much attention has being paid to the classification module, while candidate generation has mainly relied on (multiscale) sliding window pyramid. However, candidate generation is critical for achieving real-time. In this paper we assume a context of autonomous driving based on stereo vision. Accordingly, we evaluate the effect of taking into account the 3D information (derived from the stereo) in order to prune the hundred of thousands windows per image generated by classical pyramidal sliding window. For our study we use a multimodal (RGB, disparity) and multi-descriptor (HOG, LBP, HOG+LBP) holistic ensemble based on linear SVM. Evaluation on data from the challenging KITTI benchmark suite shows the effectiveness of using 3D information to dramatically reduce the number of candidate windows, even improving the overall pedestrian detection accuracy.  
  Address Santiago de Compostela; España; June 2015  
  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 ACDC Expedition Conference IbPRIA  
  Notes ADAS; 600.076; 600.057; 600.054 Approved no  
  Call Number ADAS @ adas @ GVR2015 Serial 2585  
Permanent link to this record
 

 
Author Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez edit   pdf
url  openurl
  Title Factorization with Missing and Noisy Data Type Conference Article
  Year 2006 Publication 6th International Conference on Computational Science Abbreviated Journal ICCS´06  
  Volume LNCS 3991 Issue Pages (down) 555–562  
  Keywords  
  Abstract  
  Address Reading (United Kingdom)  
  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 ADAS @ adas @ JSL2006b Serial 653  
Permanent link to this record
 

 
Author David Geronimo; Antonio Lopez; Angel Sappa edit   pdf
url  openurl
  Title Computer Vision Approaches for Pedestrian Detection: Visible Spectrum Survey Type Conference Article
  Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 Abbreviated Journal  
  Volume 1 Issue Pages (down) 547–554  
  Keywords Pedestrian detection  
  Abstract Pedestrian detection from images of the visible spectrum is a high relevant area of research given its potential impact in the design of pedestrian protection systems. There are many proposals in the literature but they lack a comparative viewpoint. According to this, in this paper we first propose a common framework where we fit the different approaches, and second we use this framework to provide a comparative point of view of the details of such different approaches, pointing out also the main challenges to be solved in the future. In summary, we expect
this survey to be useful for both novel and experienced researchers in the field. In the first case, as a clarifying snapshot of the state of the art; in the second, as a way to unveil trends and to take conclusions from the comparative study.
 
  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  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ GLS2007 Serial 804  
Permanent link to this record
Select All    Deselect All
 |   | 
Details

Save Citations:
Export Records: