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Author |
Antonio Lopez; Joan Serrat; Cristina Cañero; Felipe Lumbreras |
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Title |
Robust Lane Lines Detection and Quantitative Assessment |
Type |
Conference Article |
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Year |
2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis |
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Volume |
4477 |
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Pages |
274–281 |
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Keywords |
lane markings |
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Girona (Spain) |
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J. Marti et al |
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IbPRIA |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ LSC2007 |
Serial |
881 |
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Author |
David Lloret; Joan Serrat; Antonio Lopez; A. Soler; Juan J. Villanueva |
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Title |
Retinal image registration using creases as anatomical landmarks. |
Type |
Conference Article |
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Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
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Volume |
3 |
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Pages |
207-2010 |
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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 |
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Barcelona. |
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ICPR |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ LSL2000 c |
Serial |
233 |
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Author |
Judit Martinez; Eva Costa; P. Herreros; Antonio Lopez; Juan J. Villanueva |
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Title |
TV-Screen Quality Inspection by Artificial Vision |
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Conference Article |
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Year |
2003 |
Publication |
Proceedings SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision (QCAV 2003) |
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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. |
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Gatlinburg, (EEUU) |
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ADAS |
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no |
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ADAS @ adas @ MCH2003a |
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393 |
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Author |
Javier Marin; David Vazquez; David Geronimo; Antonio Lopez |
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Title |
Learning Appearance in Virtual Scenarios for Pedestrian Detection |
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Conference Article |
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Year |
2010 |
Publication |
23rd IEEE Conference on Computer Vision and Pattern Recognition |
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Pages |
137–144 |
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Keywords |
Pedestrian Detection; Domain Adaptation |
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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. |
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San Francisco; CA; USA; June 2010 |
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English |
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English |
Original Title |
Learning Appearance in Virtual Scenarios for Pedestrian Detection |
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ISSN |
1063-6919 |
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978-1-4244-6984-0 |
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CVPR |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ MVG2010 |
Serial |
1304 |
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Author |
Javier Marin; David Vazquez; Antonio Lopez; Jaume Amores; Bastian Leibe |
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Title |
Random Forests of Local Experts for Pedestrian Detection |
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Conference Article |
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Year |
2013 |
Publication |
15th IEEE International Conference on Computer Vision |
Abbreviated Journal |
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Pages |
2592 - 2599 |
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Keywords |
ADAS; Random Forest; Pedestrian Detection |
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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. |
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Sydney; Australia; December 2013 |
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IEEE |
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1550-5499 |
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ICCV |
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Notes |
ADAS; 600.057; 600.054 |
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no |
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Call Number |
ADAS @ adas @ MVL2013 |
Serial |
2333 |
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Permanent link to this record |
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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 |
Type |
Conference Article |
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Year |
2012 |
Publication |
International Conference on Intelligent Robots and Systems |
Abbreviated Journal |
IROS |
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Pages |
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 |
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no |
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Call Number |
ADAS @ adas @ NRR2012 |
Serial |
2378 |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow |
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Conference Article |
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Year |
2010 |
Publication |
7th International Conference on Image Analysis and Recognition |
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Volume |
6111 |
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Pages |
230-239 |
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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. |
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Address |
Povoa de Varzim (Portugal) |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-13771-6 |
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ICIAR |
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ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ OnS2010 |
Serial |
1342 |
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Permanent link to this record |
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Author |
A. Pujol; Felipe Lumbreras; Javier Varona; Juan J. Villanueva |
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Title |
Locating people in indoor scenes for real applications. |
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Conference Article |
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Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
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4 |
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632-635 |
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Barcelona. |
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ICPR |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ PLV2000 |
Serial |
237 |
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Author |
Daniel Ponsa; Antonio Lopez |
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Title |
Vehicle Trajectory Estimation based on Monocular Vision |
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Conference Article |
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Year |
2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 |
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587-594 |
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vehicle detection |
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Girona (Spain) |
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ADAS |
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no |
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ADAS @ adas @ PoL2007a |
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785 |
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Author |
Daniel Ponsa; Antonio Lopez |
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Title |
Feature Selection Based on a New Formulation of the Minimal-Redundancy-Maximal-Relevance Criterion |
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Conference Article |
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Year |
2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 |
Abbreviated Journal |
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47-54 |
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Girona (Spain) |
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ADAS |
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no |
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ADAS @ adas @ PoL2007b |
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787 |
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Author |
Daniel Ponsa; Antonio Lopez |
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Title |
Cascade of Classifiers for Vehicle Detection |
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Conference Article |
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2007 |
Publication |
Advanced Concepts for Intelligent Vision Systems, LNCS 4678, volume 1, pp. 980–989 |
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vehicle detection |
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Address |
Delft (Netherlands) |
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ADAS |
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no |
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ADAS @ adas @ PoL2007c |
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935 |
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Author |
Petia Radeva; Joan Serrat |
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Title |
Rubber Snake: Implementation on Signed Distance Potential. |
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Conference Article |
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1993 |
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Vision Conference |
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187-194 |
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Zurich, Switzerland. |
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SWISS |
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ADAS;MILAB |
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no |
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ADAS @ adas @ RaS1993 |
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170 |
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Author |
Gemma Roig; Xavier Boix; R. de Nijs; Sebastian Ramos; K. Kühnlenz; Luc Van Gool |
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Title |
Active MAP Inference in CRFs for Efficient Semantic Segmentation |
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Conference Article |
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2013 |
Publication |
15th IEEE International Conference on Computer Vision |
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2312 - 2319 |
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Semantic Segmentation |
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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. |
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Sydney; Australia; December 2013 |
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1550-5499 |
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ICCV |
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ADAS; 600.057 |
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no |
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ADAS @ adas @ RBN2013 |
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2377 |
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Permanent link to this record |
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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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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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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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Bordeaux, France |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-04696-4 |
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ACIVS |
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ADAS |
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no |
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ADAS @ adas @ RoS2009 |
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1194 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
Relaxing the 3L Algorithm for an Accurate Implicit Polynomial Fitting |
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Conference Article |
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2010 |
Publication |
23rd IEEE Conference on Computer Vision and Pattern Recognition |
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3066-3072 |
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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. |
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San Francisco; CA; USA; June 2010 |
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1063-6919 |
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978-1-4244-6984-0 |
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CVPR |
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ADAS |
Approved |
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ADAS @ adas @ RoS2010a |
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1303 |
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