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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat |
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Title |
Photometric Stereo through and Adapted Alternation Approach |
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Conference Article |
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Year |
2008 |
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IEEE International Conference on Image Processing, |
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1500–1503 |
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San Diego; CA; USA |
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ADAS |
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ADAS @ adas @ JSL2008d |
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1016 |
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Author |
Angel Sappa; Fadi Dornaika; David Geronimo; Antonio Lopez |
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Title |
Registration-based Moving Object Detection from a Moving Camera |
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Conference Article |
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Year |
2008 |
Publication |
IROS2008 2nd Workshop on Perception, Planning and Navigation for Intelligent Vehicles |
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65–69 |
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This paper presents a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three stages. Initially, feature points are extracted and tracked through consecutive frames. Then, a RANSAC based approach is used for registering
two 3D point sets with known correspondences by means of the quaternion method. Finally, the computed 3D rigid displacement is used to map two consecutive frames into the same coordinate system. Moving objects correspond to those areas with large registration errors. Experimental results, in different scenarios, show the viability of the proposed approach. |
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Nice (France) |
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Call Number |
ADAS @ adas @ SDG2008 |
Serial |
1017 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
An Adapted Alternation Approach for Recommender Systems |
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Conference Article |
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Year |
2008 |
Publication |
IEEE International Conference on e–Business Engineering, |
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128–135 |
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This paper presents an adaptation of the alternation technique to tackle the prediction task in recommender systems. These systems are widely considered in electronic commerce to help customers to find products they will probably like or dislike. As the SVD-based approaches, the proposed adapted alternation technique uses all the information stored in the system to find the predictions. The main advantage of this technique with respect to the SVD-based ones is that it can deal with missing data. Furthermore, it has a smaller computational cost. Experimental results with public data sets are provided in order to show the viability of the proposed adapted alternation approach. |
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Xi’an (Xina) |
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ADAS @ adas @ JSL2008e |
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1044 |
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Author |
Jose Manuel Alvarez; Antonio Lopez; Ramon Baldrich |
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Title |
Illuminant Invariant Model-Based Road Segmentation |
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Conference Article |
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Year |
2008 |
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IEEE Intelligent Vehicles Symposium, |
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1155–1180 |
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Keywords |
road detection |
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Eindhoven (The Netherlands) |
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ADAS;CIC |
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Call Number |
ADAS @ adas @ ALB2008 |
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1045 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Improving Appearance-Based 3D Face Tracking Using Sparse Stereo Data |
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Conference Article |
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Year |
2007 |
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Advances in Computer Graphics and Computer Vision, |
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354–366 |
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Springer Verlag |
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J. Braz, A. Ranchordas, H. Araujo and J. Jorge, |
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VISAPP |
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ADAS |
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Call Number |
ADAS @ adas @ DoS2007d |
Serial |
1046 |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Novel Index for Objective Evaluation of Road Detection Algorithms |
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Conference Article |
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Year |
2008 |
Publication |
Intelligent Transportation Systems. 11th International IEEE Conference on, |
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815–820 |
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road detection |
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Address |
Beijing (Xina) |
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ITSC |
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ADAS |
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ADAS @ adas @ AlL2008 |
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1074 |
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Author |
Antonio Lopez; J. Hilgenstock; A. Busse; Ramon Baldrich; Felipe Lumbreras; Joan Serrat |
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Title |
Nightime Vehicle Detecion for Intelligent Headlight Control |
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Conference Article |
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Year |
2008 |
Publication |
Advanced Concepts for Intelligent Vision Systems, 10th International Conference, Proceedings, |
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5259 |
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113–124 |
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Intelligent Headlights; vehicle detection |
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Juan-les-Pins, France |
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LNCS |
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ACIVS |
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ADAS;CIC |
Approved |
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ADAS @ adas @ LHB2008a |
Serial |
1098 |
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Author |
Arnau Ramisa; Adriana Tapus; Ramon Lopez de Mantaras; Ricardo Toledo |
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Title |
Mobile Robot Localization using Panoramic Vision and Combination of Feature Region Detectors |
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Conference Article |
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Year |
2008 |
Publication |
IEEE International Conference on Robotics and Automation, |
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538–543 |
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Pasadena; CA; USA |
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ICRA |
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RV;ADAS |
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Admin @ si @ RTL2008 |
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1144 |
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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 |
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Title |
Combining local and global bag-of-word representations for semantic segmentation |
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Conference Article |
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Year |
2009 |
Publication |
Workshop on The PASCAL Visual Object Classes Challenge |
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Kyoto (Japan) |
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ICCV |
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ADAS;ISE |
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ADAS @ adas @ BGS2009 |
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1273 |
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Author |
R. de Nijs; Sebastian Ramos; Gemma Roig; Xavier Boix; Luc Van Gool; K. Kühnlenz. |
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Title |
On-line Semantic Perception Using Uncertainty |
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Conference Article |
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2012 |
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International Conference on Intelligent Robots and Systems |
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IROS |
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4185-4191 |
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Keywords |
Semantic Segmentation |
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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 |
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IROS |
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ADAS @ adas @ NRR2012 |
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2378 |
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