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Author |
Karel Paleček; David Geronimo; Frederic Lerasle |
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Title |
Pre-attention cues for person detection |
Type |
Conference Article |
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Year |
2012 |
Publication |
Cognitive Behavioural Systems, COST 2102 International Training School |
Abbreviated Journal |
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Pages  |
225-235 |
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Abstract |
Current state-of-the-art person detectors have been proven reliable and achieve very good detection rates. However, the performance is often far from real time, which limits their use to low resolution images only. In this paper, we deal with candidate window generation problem for person detection, i.e. we want to reduce the computational complexity of a person detector by reducing the number of regions that has to be evaluated. We base our work on Alexe’s paper [1], which introduced several pre-attention cues for generic object detection. We evaluate these cues in the context of person detection and show that their performance degrades rapidly for scenes containing multiple objects of interest such as pictures from urban environment. We extend this set by new cues, which better suits our class-specific task. The cues are designed to be simple and efficient, so that they can be used in the pre-attention phase of a more complex sliding window based person detector. |
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Address |
Dresden, Germany |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-34583-8 |
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COST-TS |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ PGL2012 |
Serial |
2148 |
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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 |
Type |
Conference Article |
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Year |
2010 |
Publication |
7th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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Volume |
6111 |
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Pages |
230-239 |
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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. |
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Address |
Povoa de Varzim (Portugal) |
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Publisher |
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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Conference |
ICIAR |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ OnS2010 |
Serial |
1342 |
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Author |
Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen |
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Title |
Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging |
Type |
Conference Article |
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Year |
2014 |
Publication |
17th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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Volume |
8896 |
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Pages |
231-238 |
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Keywords |
Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging |
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Abstract |
Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across di erent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three di erent OF methods, including HARP. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-319-14677-5 |
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Conference |
STACOM |
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Notes |
IAM; ADAS; 600.060; 601.145; 600.076; 600.075 |
Approved |
no |
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Call Number |
Admin @ si @ MKF2014 |
Serial |
2495 |
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Author |
German Ros; Sebastian Ramos; Manuel Granados; Amir Bakhtiary; David Vazquez; Antonio Lopez |
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Title |
Vision-based Offline-Online Perception Paradigm for Autonomous Driving |
Type |
Conference Article |
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Year |
2015 |
Publication |
IEEE Winter Conference on Applications of Computer Vision |
Abbreviated Journal |
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Pages |
231 - 238 |
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Keywords |
Autonomous Driving; Scene Understanding; SLAM; Semantic Segmentation |
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Abstract |
Autonomous driving is a key factor for future mobility. Properly perceiving the environment of the vehicles is essential for a safe driving, which requires computing accurate geometric and semantic information in real-time. In this paper, we challenge state-of-the-art computer vision algorithms for building a perception system for autonomous driving. An inherent drawback in the computation of visual semantics is the trade-off between accuracy and computational cost. We propose to circumvent this problem by following an offline-online strategy. During the offline stage dense 3D semantic maps are created. In the online stage the current driving area is recognized in the maps via a re-localization process, which allows to retrieve the pre-computed accurate semantics and 3D geometry in realtime. Then, detecting the dynamic obstacles we obtain a rich understanding of the current scene. We evaluate quantitatively our proposal in the KITTI dataset and discuss the related open challenges for the computer vision community. |
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Hawaii; January 2015 |
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ACDC |
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Conference |
WACV |
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Notes |
ADAS; 600.076 |
Approved |
no |
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Call Number |
ADAS @ adas @ RRG2015 |
Serial |
2499 |
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Author |
Felipe Codevilla; Antonio Lopez; Vladlen Koltun; Alexey Dosovitskiy |
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Title |
On Offline Evaluation of Vision-based Driving Models |
Type |
Conference Article |
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Year |
2018 |
Publication |
15th European Conference on Computer Vision |
Abbreviated Journal |
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Volume |
11219 |
Issue |
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Pages |
246-262 |
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Keywords |
Autonomous driving; deep learning |
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Abstract |
Autonomous driving models should ideally be evaluated by deploying
them on a fleet of physical vehicles in the real world. Unfortunately, this approach is not practical for the vast majority of researchers. An attractive alternative is to evaluate models offline, on a pre-collected validation dataset with ground truth annotation. In this paper, we investigate the relation between various online and offline metrics for evaluation of autonomous driving models. We find that offline prediction error is not necessarily correlated with driving quality, and two models with identical prediction error can differ dramatically in their driving performance. We show that the correlation of offline evaluation with driving quality can be significantly improved by selecting an appropriate validation dataset and
suitable offline metrics. |
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Address |
Munich; September 2018 |
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LNCS |
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Conference |
ECCV |
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Notes |
ADAS; 600.124; 600.118 |
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no |
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Call Number |
Admin @ si @ CLK2018 |
Serial |
3162 |
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Author |
Naveen Onkarappa; Sujay M. Veerabhadrappa; Angel Sappa |
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Title |
Optical Flow in Onboard Applications: A Study on the Relationship Between Accuracy and Scene Texture |
Type |
Conference Article |
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Year |
2012 |
Publication |
4th International Conference on Signal and Image Processing |
Abbreviated Journal |
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Volume |
221 |
Issue |
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Pages |
257-267 |
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Abstract |
Optical flow has got a major role in making advanced driver assistance systems (ADAS) a reality. ADAS applications are expected to perform efficiently in all kinds of environments, those are highly probable, that one can drive the vehicle in different kinds of roads, times and seasons. In this work, we study the relationship of optical flow with different roads, that is by analyzing optical flow accuracy on different road textures. Texture measures such as TeX , TeX and TeX are evaluated for this purpose. Further, the relation of regularization weight to the flow accuracy in the presence of different textures is also analyzed. Additionally, we present a framework to generate synthetic sequences of different textures in ADAS scenarios with ground-truth optical flow. |
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Address |
Coimbatore, India |
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ISSN |
1876-1100 |
ISBN |
978-81-322-0996-6 |
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Conference |
ICSIP |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ OVS2012 |
Serial |
2356 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
Non-Rigid Shape Registration: A Single Linear Least Squares Framework |
Type |
Conference Article |
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Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal |
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Volume |
7578 |
Issue |
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Pages |
264-277 |
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Abstract |
This paper proposes a non-rigid registration formulation capturing both global and local deformations in a single framework. This formulation is based on a quadratic estimation of the registration distance together with a quadratic regularization term. Hence, the optimal transformation parameters are easily obtained by solving a liner system of equations, which guarantee a fast convergence. Experimental results with challenging 2D and 3D shapes are presented to show the validity of the proposed framework. Furthermore, comparisons with the most relevant approaches are provided. |
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Address |
Florencia |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-33785-7 |
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Conference |
ECCV |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RoS2012a |
Serial |
2158 |
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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 |
Abbreviated Journal |
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Volume |
4477 |
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Pages |
274–281 |
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Keywords |
lane markings |
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Address |
Girona (Spain) |
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Editor |
J. Marti et al |
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LNCS |
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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 |
Arnau Ramisa; Ramon Lopez de Mantaras; Ricardo Toledo |
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Title |
Comparing Combinations of Feature Regions for Panoramic VSLAM |
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Conference Article |
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Year |
2007 |
Publication |
4th International Conference on Informatics in Control, Automation and Robotics |
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Pages |
292–297 |
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Address |
Angers (France) |
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ICINCO |
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Notes |
RV;ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RLA2007 |
Serial |
900 |
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Author |
Miguel Oliveira; Angel Sappa; V. Santos |
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Title |
Color Correction for Onboard Multi-camera Systems using 3D Gaussian Mixture Models |
Type |
Conference Article |
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Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
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Pages |
299-303 |
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Abstract |
The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches. |
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Address |
Alcalá de Henares |
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Publisher |
IEEE Xplore |
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ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
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Conference |
IV |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ OSS2012b |
Serial |
2021 |
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