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Author |
Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados |
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Title |
Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans |
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Conference Article |
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Year |
2013 |
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10th IAPR International Workshop on Graphics Recognition |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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DAG; 600.045; 600.061; 600.056 |
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Admin @ si @ HFF2013b |
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2695 |
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Author |
Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez |
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Title |
Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies |
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Conference Article |
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2013 |
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10th IAPR International Workshop on Graphics Recognition |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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DAG |
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Admin @ si @ HVS2013b |
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2696 |
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Author |
A.S. Coquel; Jean-Pascal Jacob; M. Primet; A. Demarez; Mariella Dimiccoli; T. Julou; L. Moisan; A. Lindner; H. Berry |
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Title |
Localization of protein aggregation in Escherichia coli is governed by diffusion and nucleoid macromolecular crowding effect |
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Journal Article |
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Year |
2013 |
Publication |
Plos Computational Biology |
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PCB |
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9 |
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4 |
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Aggregates of misfolded proteins are a hallmark of many age-related diseases. Recently, they have been linked to aging of Escherichia coli (E. coli) where protein aggregates accumulate at the old pole region of the aging bacterium. Because of the potential of E. coli as a model organism, elucidating aging and protein aggregation in this bacterium may pave the way to significant advances in our global understanding of aging. A first obstacle along this path is to decipher the mechanisms by which protein aggregates are targeted to specific intercellular locations. Here, using an integrated approach based on individual-based modeling, time-lapse fluorescence microscopy and automated image analysis, we show that the movement of aging-related protein aggregates in E. coli is purely diffusive (Brownian). Using single-particle tracking of protein aggregates in live E. coli cells, we estimated the average size and diffusion constant of the aggregates. Our results provide evidence that the aggregates passively diffuse within the cell, with diffusion constants that depend on their size in agreement with the Stokes-Einstein law. However, the aggregate displacements along the cell long axis are confined to a region that roughly corresponds to the nucleoid-free space in the cell pole, thus confirming the importance of increased macromolecular crowding in the nucleoids. We thus used 3D individual-based modeling to show that these three ingredients (diffusion, aggregation and diffusion hindrance in the nucleoids) are sufficient and necessary to reproduce the available experimental data on aggregate localization in the cells. Taken together, our results strongly support the hypothesis that the localization of aging-related protein aggregates in the poles of E. coli results from the coupling of passive diffusion-aggregation with spatially non-homogeneous macromolecular crowding. They further support the importance of “soft” intracellular structuring (based on macromolecular crowding) in diffusion-based protein localization in E. coli. |
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: Stanislav Shvartsman, Princeton University, United States of America |
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Admin @ si @CJP2013 |
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2786 |
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Author |
Mariella Dimiccoli; Benoît Girard; Alain Berthoz; Daniel Bennequin |
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Title |
Striola Magica: a functional explanation of otolith organs |
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Journal Article |
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Year |
2013 |
Publication |
Journal of Computational Neuroscience |
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JCN |
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35 |
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2 |
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125-154 |
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Keywords |
Otolith organs ;Striola; Vestibular pathway |
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Abstract |
Otolith end organs of vertebrates sense linear accelerations of the head and gravitation. The hair cells on their epithelia are responsible for transduction. In mammals, the striola, parallel to the line where hair cells reverse their polarization, is a narrow region centered on a curve with curvature and torsion. It has been shown that the striolar region is functionally different from the rest, being involved in a phasic vestibular pathway. We propose a mathematical and computational model that explains the necessity of this amazing geometry for the striola to be able to carry out its function. Our hypothesis, related to the biophysics of the hair cells and to the physiology of their afferent neurons, is that striolar afferents collect information from several type I hair cells to detect the jerk in a large domain of acceleration directions. This predicts a mean number of two calyces for afferent neurons, as measured in rodents. The domain of acceleration directions sensed by our striolar model is compatible with the experimental results obtained on monkeys considering all afferents. Therefore, the main result of our study is that phasic and tonic vestibular afferents cover the same geometrical fields, but at different dynamical and frequency domains. |
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Springer US |
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1573-6873. 2013 |
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MILAB |
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no |
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Admin @ si @DBG2013 |
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2787 |
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Author |
Jose Manuel Alvarez; Theo Gevers; Antonio Lopez |
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Title |
Evaluating Color Representation for Online Road Detection |
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Conference Article |
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Year |
2013 |
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ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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594-595 |
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Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired
using an on-board camera in different real-driving situations. |
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CVVT:E2M |
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ADAS;ISE |
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Admin @ si @ AGL2013 |
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2794 |
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Author |
David Vazquez |
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Title |
Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection |
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Book Whole |
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Year |
2013 |
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PhD Thesis, Universitat de Barcelona-CVC |
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1 |
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1 |
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1-105 |
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Pedestrian Detection; Domain Adaptation |
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Pedestrian detection is of paramount interest for many applications, e.g. Advanced Driver Assistance Systems, Intelligent Video Surveillance and Multimedia systems. Most promising pedestrian detectors rely on appearance-based classifiers trained with annotated data. However, the required annotation step represents an intensive and subjective task for humans, what makes worth to minimize their intervention in this process by using computational tools like realistic virtual worlds. The reason to use these kind of tools relies in the fact that they allow the automatic generation of precise and rich annotations of visual information. Nevertheless, the use of this kind of data comes with the following question: can a pedestrian appearance model learnt with virtual-world data work successfully for pedestrian detection in real-world scenarios?. To answer this question, we conduct different experiments that suggest a positive answer. However, the pedestrian classifiers trained with virtual-world data can suffer the so called dataset shift problem as real-world based classifiers does. Accordingly, we have designed different domain adaptation techniques to face this problem, all of them integrated in a same framework (V-AYLA). We have explored different methods to train a domain adapted pedestrian classifiers by collecting a few pedestrian samples from the target domain (real world) and combining them with many samples of the source domain (virtual world). The extensive experiments we present show that pedestrian detectors developed within the V-AYLA framework do achieve domain adaptation. Ideally, we would like to adapt our system without any human intervention. Therefore, as a first proof of concept we also propose an unsupervised domain adaptation technique that avoids human intervention during the adaptation process. To the best of our knowledge, this Thesis work is the first demonstrating adaptation of virtual and real worlds for developing an object detector. Last but not least, we also assessed a different strategy to avoid the dataset shift that consists in collecting real-world samples and retrain with them in such a way that no bounding boxes of real-world pedestrians have to be provided. We show that the generated classifier is competitive with respect to the counterpart trained with samples collected by manually annotating pedestrian bounding boxes. The results presented on this Thesis not only end with a proposal for adapting a virtual-world pedestrian detector to the real world, but also it goes further by pointing out a new methodology that would allow the system to adapt to different situations, which we hope will provide the foundations for future research in this unexplored area. |
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Barcelona |
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Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
Barcelona |
Editor |
Antonio Lopez;Daniel Ponsa |
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English |
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978-84-940530-1-6 |
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adas |
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yes |
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Call Number |
ADAS @ adas @ Vaz2013 |
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2276 |
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Author |
Jiaolong Xu; David Vazquez; Sebastian Ramos; Antonio Lopez; Daniel Ponsa |
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Title |
Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers |
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Conference Article |
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2013 |
Publication |
CVPR Workshop on Ground Truth – What is a good dataset? |
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688 - 693 |
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Pedestrian Detection; Domain Adaptation |
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Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%. |
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Portland; oregon; June 2013 |
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English |
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CVPRW |
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ADAS; 600.054; 600.057; 601.217 |
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yes |
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Call Number |
XVR2013; ADAS @ adas @ xvr2013a |
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2220 |
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