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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Antonio Lopez |
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Title |
Recovery of Surface Normals and Reflectance from Different Lighting Conditions |
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Conference Article |
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Year |
2008 |
Publication |
5th International Conference on Image Analysis and Recognition |
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5112 |
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315–325 |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ JSL2008c |
Serial |
1014 |
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Author |
Aura Hernandez-Sabate; Lluis Albarracin; Daniel Calvo; Nuria Gorgorio |
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Title |
EyeMath: Identifying Mathematics Problem Solving Processes in a RTS Video Game |
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Conference Article |
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Year |
2016 |
Publication |
5th International Conference Games and Learning Alliance |
Abbreviated Journal |
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Volume |
10056 |
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Pages |
50-59 |
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Keywords |
Simulation environment; Automated Driving; Driver-Vehicle interaction |
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Abstract |
Photorealistic virtual environments are crucial for developing and testing automated driving systems in a safe way during trials. As commercially available simulators are expensive and bulky, this paper presents a low-cost, extendable, and easy-to-use (LEE) virtual environment with the aim to highlight its utility for level 3 driving automation. In particular, an experiment is performed using the presented simulator to explore the influence of different variables regarding control transfer of the car after the system was driving autonomously in a highway scenario. The results show that the speed of the car at the time when the system needs to transfer the control to the human driver is critical. |
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GALA |
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ADAS;IAM; |
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no |
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Call Number |
HAC2016 |
Serial |
2864 |
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Author |
Muhammad Anwer Rao; David Vazquez; Antonio Lopez |
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Title |
Opponent Colors for Human Detection |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
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Pages |
363-370 |
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Keywords |
Pedestrian Detection; Color; Part Based Models |
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Abstract |
Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper. |
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Las Palmas de Gran Canaria. Spain |
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Springer |
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Berlin Heidelberg |
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J. Vitria; J.M. Sanches; M. Hernandez |
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English |
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English |
Original Title |
Opponent Colors for Human Detection |
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Lecture Notes on Computer Science |
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ISSN |
0302-9743 |
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978-3-642-21256-7 |
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IbPRIA |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ RVL2011a |
Serial |
1666 |
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Author |
Hanne Kause; Patricia Marquez; Andrea Fuster; Aura Hernandez-Sabate; Luc Florack; Debora Gil; Hans van Assen |
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Title |
Quality Assessment of Optical Flow in Tagging MRI |
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Conference Article |
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Year |
2015 |
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5th Dutch Bio-Medical Engineering Conference BME2015 |
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The Netherlands; January 2015 |
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BME |
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IAM; ADAS; 600.076; 600.075 |
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no |
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Admin @ si @ KMF2015 |
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2616 |
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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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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 |
Monica Piñol; Angel Sappa; Ricardo Toledo |
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Title |
MultiTable Reinforcement for Visual Object Recognition |
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 |
469-480 |
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Abstract |
This paper presents a bag of feature based method for visual object recognition. Our contribution is focussed on the selection of the best feature descriptor. It is implemented by using a novel multi-table reinforcement learning method that selects among five of classical descriptors (i.e., Spin, SIFT, SURF, C-SIFT and PHOW) the one that best describes each image. Experimental results and comparisons are provided showing the improvements achieved with the proposed approach. |
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Coimbatore, India |
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Springer India |
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1876-1100 |
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978-81-322-0996-6 |
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ICSIP |
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ADAS |
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no |
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Call Number |
Admin @ si @ PST2012 |
Serial |
2157 |
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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 |
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no |
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Call Number |
Admin @ si @ RLA2007 |
Serial |
900 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
Motion Segmentation from Feature Trajectories with Missing Data |
Type |
Conference Article |
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Year |
2007 |
Publication |
3rd. Iberian Conference on Pattern Recognition and Image Analysis |
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IbPRIA 2007 |
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LNCS 4477 |
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Pages |
483–490 |
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Address |
Girona (Spain) |
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J. Marti et al. (Eds.) |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ JSL2007a |
Serial |
814 |
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Author |
Konstantia Georgouli; Katerine Diaz; Jesus Martinez del Rincon; Anastasios Koidis |
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Title |
Building generic, easily-updatable chemometric models with harmonisation and augmentation features: The case of FTIR vegetable oils classification |
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Conference Article |
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2017 |
Publication |
3rd Ιnternational Conference Metrology Promoting Standardization and Harmonization in Food and Nutrition |
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Thessaloniki; Greece; October 2017 |
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IMEKOFOODS |
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ADAS; 600.118 |
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no |
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Admin @ si @ GDM2017 |
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3081 |
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Author |
Jaume Amores; David Geronimo; Antonio Lopez |
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Title |
Multiple instance and active learning for weakly-supervised object-class segmentation |
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Conference Article |
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Year |
2010 |
Publication |
3rd IEEE International Conference on Machine Vision |
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Multiple Instance Learning; Active Learning; Object-class segmentation. |
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Abstract |
In object-class segmentation, one of the most tedious tasks is to manually segment many object examples in order to learn a model of the object category. Yet, there has been little research on reducing the degree of manual annotation for
object-class segmentation. In this work we explore alternative strategies which do not require full manual segmentation of the object in the training set. In particular, we study the use of bounding boxes as a coarser and much cheaper form of segmentation and we perform a comparative study of several Multiple-Instance Learning techniques that allow to obtain a model with this type of weak annotation. We show that some of these methods can be competitive, when used with coarse
segmentations, with methods that require full manual segmentation of the objects. Furthermore, we show how to use active learning combined with this weakly supervised strategy.
As we see, this strategy permits to reduce the amount of annotation and optimize the number of examples that require full manual segmentation in the training set. |
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Hong-Kong |
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ICMV |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ AGL2010b |
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1429 |
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