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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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Keywords |
road detection |
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Beijing (Xina) |
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ITSC |
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ADAS |
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ADAS @ adas @ AlL2008 |
Serial |
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 |
Type |
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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Pages |
113–124 |
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Keywords |
Intelligent Headlights; vehicle detection |
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Juan-les-Pins, France |
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ACIVS |
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ADAS;CIC |
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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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no |
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Call Number |
Admin @ si @ RTL2008 |
Serial |
1144 |
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Author |
Jose Manuel Alvarez; Theo Gevers; Antonio Lopez |
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Title |
Learning Photometric Invariance from Diversified Color Model Ensembles |
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Conference Article |
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Year |
2009 |
Publication |
22nd IEEE Conference on Computer Vision and Pattern Recognition |
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565–572 |
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Keywords |
road detection |
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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. |
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Address |
Miami (USA) |
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1063-6919 |
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978-1-4244-3992-8 |
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Conference |
CVPR |
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ADAS;ISE |
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ADAS @ adas @ AGL2009 |
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1169 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
A Novel Approach to Geometric Fitting of Implicit Quadrics |
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Conference Article |
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Year |
2009 |
Publication |
8th International Conference on Advanced Concepts for Intelligent Vision Systems |
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5807 |
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121–132 |
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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. |
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Address |
Bordeaux, France |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-04696-4 |
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ADAS |
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Call Number |
ADAS @ adas @ RoS2009 |
Serial |
1194 |
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Author |
Jose Manuel Alvarez; Ferran Diego; Joan Serrat; Antonio Lopez |
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Title |
Automatic Ground-truthing using video registration for on-board detection algorithms |
Type |
Conference Article |
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Year |
2009 |
Publication |
16th IEEE International Conference on Image Processing |
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Pages |
4389 - 4392 |
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Abstract |
Ground-truth data is essential for the objective evaluation of object detection methods in computer vision. Many works claim their method is robust but they support it with experiments which are not quantitatively assessed with regard some ground-truth. This is one of the main obstacles to properly evaluate and compare such methods. One of the main reasons is that creating an extensive and representative ground-truth is very time consuming, specially in the case of video sequences, where thousands of frames have to be labelled. Could such a ground-truth be generated, at least in part, automatically? Though it may seem a contradictory question, we show that this is possible for the case of video sequences recorded from a moving camera. The key idea is transferring existing frame segmentations from a reference sequence into another video sequence recorded at a different time on the same track, possibly under a different ambient lighting. We have carried out experiments on several video sequence pairs and quantitatively assessed the precision of the transformed ground-truth, which prove that our approach is not only feasible but also quite accurate. |
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Cairo, Egypt |
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1522-4880 |
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978-1-4244-5653-6 |
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ICIP |
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ADAS |
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Call Number |
ADAS @ adas @ ADS2009 |
Serial |
1201 |
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Author |
Angel Sappa; Mohammad Rouhani |
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Title |
Efficient Distance Estimation for Fitting Implicit Quadric Surfaces |
Type |
Conference Article |
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Year |
2009 |
Publication |
16th IEEE International Conference on Image Processing |
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Pages |
3521–3524 |
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Abstract |
This paper presents a novel approach for estimating the shortest Euclidean distance from a given point to the corresponding implicit quadric fitting surface. It first estimates the orthogonal orientation to the surface from the given point; then the shortest distance is directly estimated by intersecting the implicit surface with a line passing through the given point according to the estimated orthogonal orientation. The proposed orthogonal distance estimation is easily obtained without increasing computational complexity; hence it can be used in error minimization surface fitting frameworks. Comparisons of the proposed metric with previous approaches are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. Surfaces fitted by using the proposed geometric distance estimation and state of the art metrics are presented to show the viability of the proposed approach. |
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Cairo, Egypt |
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1522-4880 |
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978-1-4244-5653-6 |
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ICIP |
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ADAS |
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ADAS @ adas @ SaR2009 |
Serial |
1232 |
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Author |
Ariel Amato; Angel Sappa; Alicia Fornes; Felipe Lumbreras; Josep Llados |
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Title |
Divide and Conquer: Atomizing and Parallelizing A Task in A Mobile Crowdsourcing Platform |
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Conference Article |
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Year |
2013 |
Publication |
2nd International ACM Workshop on Crowdsourcing for Multimedia |
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21-22 |
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In this paper we present some conclusions about the advantages of having an efficient task formulation when a crowdsourcing platform is used. In particular we show how the task atomization and distribution can help to obtain results in an efficient way. Our proposal is based on a recursive splitting of the original task into a set of smaller and simpler tasks. As a result both more accurate and faster solutions are obtained. Our evaluation is performed on a set of ancient documents that need to be digitized. |
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Barcelona; October 2013 |
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978-1-4503-2396-3 |
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CrowdMM |
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ADAS; ISE; DAG; 600.054; 600.055; 600.045; 600.061; 602.006 |
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Call Number |
Admin @ si @ SLA2013 |
Serial |
2335 |
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Author |
David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras |
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Title |
Efficient Object Pixel-Level Categorization using Bag of Features: Advances in Visual Computing |
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Conference Article |
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Year |
2009 |
Publication |
5th International Symposium on Visual Computing |
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5875 |
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44–55 |
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In this paper we present a pixel-level object categorization method suitable to be applied under real-time constraints. Since pixels are categorized using a bag of features scheme, the major bottleneck of such an approach would be the feature pooling in local histograms of visual words. Therefore, we propose to bypass this time-consuming step and directly obtain the score from a linear Support Vector Machine classifier. This is achieved by creating an integral image of the components of the SVM which can readily obtain the classification score for any image sub-window with only 10 additions and 2 products, regardless of its size. Besides, we evaluated the performance of two efficient feature quantization methods: the Hierarchical K-Means and the Extremely Randomized Forest. All experiments have been done in the Graz02 database, showing comparable, or even better results to related work with a lower computational cost. |
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Address |
Las Vegas, USA |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-10330-8 |
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ISVC |
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ADAS |
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Admin @ si @ ATR2009a |
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1246 |
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Author |
David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras |
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Title |
Visual Registration Method For A Low Cost Robot: Computer Vision Systems |
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Conference Article |
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Year |
2009 |
Publication |
7th International Conference on Computer Vision Systems |
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5815 |
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204–214 |
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Abstract |
An autonomous mobile robot must face the correspondence or data association problem in order to carry out tasks like place recognition or unknown environment mapping. In order to put into correspondence two maps, most methods estimate the transformation relating the maps from matches established between low level feature extracted from sensor data. However, finding explicit matches between features is a challenging and computationally expensive task. In this paper, we propose a new method to align obstacle maps without searching explicit matches between features. The maps are obtained from a stereo pair. Then, we use a vocabulary tree approach to identify putative corresponding maps followed by the Newton minimization algorithm to find the transformation that relates both maps. The proposed method is evaluated in a typical office environment showing good performance. |
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Address |
Belgica |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-04666-7 |
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ICVS |
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ADAS |
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Call Number |
Admin @ si @ ATR2009b |
Serial |
1247 |
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