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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 |
Abbreviated Journal |
JCN |
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Volume |
35 |
Issue |
2 |
Pages |
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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Admin @ si @DBG2013 |
Serial |
2787 |
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Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
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Title |
Traffic sign recognition system with β -correction |
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Journal Article |
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Year |
2010 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
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21 |
Issue |
2 |
Pages |
99–111 |
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Traffic sign classification represents a classical application of multi-object recognition processing in uncontrolled adverse environments. Lack of visibility, illumination changes, and partial occlusions are just a few problems. In this paper, we introduce a novel system for multi-class classification of traffic signs based on error correcting output codes (ECOC). ECOC is based on an ensemble of binary classifiers that are trained on bi-partition of classes. We classify a wide set of traffic signs types using robust error correcting codings. Moreover, we introduce the novel β-correction decoding strategy that outperforms the state-of-the-art decoding techniques, classifying a high number of classes with great success. |
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Springer-Verlag |
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0932-8092 |
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MILAB;HUPBA |
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BCNPCL @ bcnpcl @ EPR2010a |
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1276 |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Personalization and User Verification in Wearable Systems using Biometric Walking Patterns |
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Journal Article |
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Year |
2012 |
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Personal and Ubiquitous Computing |
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PUC |
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16 |
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5 |
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563-580 |
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In this article, a novel technique for user’s authentication and verification using gait as a biometric unobtrusive pattern is proposed. The method is based on a two stages pipeline. First, a general activity recognition classifier is personalized for an specific user using a small sample of her/his walking pattern. As a result, the system is much more selective with respect to the new walking pattern. A second stage verifies whether the user is an authorized one or not. This stage is defined as a one-class classification problem. In order to solve this problem, a four-layer architecture is built around the geometric concept of convex hull. This architecture allows to improve robustness to outliers, modeling non-convex shapes, and to take into account temporal coherence information. Two different scenarios are proposed as validation with two different wearable systems. First, a custom high-performance wearable system is built and used in a free environment. A second dataset is acquired from an Android-based commercial device in a ‘wild’ scenario with rough terrains, adversarial conditions, crowded places and obstacles. Results on both systems and datasets are very promising, reducing the verification error rates by an order of magnitude with respect to the state-of-the-art technologies. |
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Springer-Verlag |
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1617-4909 |
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MILAB;HuPBA |
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Call Number |
Admin @ si @ CPR2012 |
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1706 |
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Author |
Eloi Puertas; Sergio Escalera; Oriol Pujol |
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Title |
Generalized Multi-scale Stacked Sequential Learning for Multi-class Classification |
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Journal Article |
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Year |
2015 |
Publication |
Pattern Analysis and Applications |
Abbreviated Journal |
PAA |
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18 |
Issue |
2 |
Pages |
247-261 |
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Keywords |
Stacked sequential learning; Multi-scale; Error-correct output codes (ECOC); Contextual classification |
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In many classification problems, neighbor data labels have inherent sequential relationships. Sequential learning algorithms take benefit of these relationships in order to improve generalization. In this paper, we revise the multi-scale sequential learning approach (MSSL) for applying it in the multi-class case (MMSSL). We introduce the error-correcting output codesframework in the MSSL classifiers and propose a formulation for calculating confidence maps from the margins of the base classifiers. In addition, we propose a MMSSL compression approach which reduces the number of features in the extended data set without a loss in performance. The proposed methods are tested on several databases, showing significant performance improvement compared to classical approaches. |
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Springer-Verlag |
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1433-7541 |
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HuPBA;MILAB |
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Call Number |
Admin @ si @ PEP2013 |
Serial |
2251 |
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Author |
Jean-Pascal Jacob; Mariella Dimiccoli; L. Moisan |
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Title |
Active skeleton for bacteria modelling |
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Journal Article |
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Year |
2017 |
Publication |
Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization |
Abbreviated Journal |
CMBBE |
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Volume |
5 |
Issue |
4 |
Pages |
274-286 |
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Abstract |
The investigation of spatio-temporal dynamics of bacterial cells and their molecular components requires automated image analysis tools to track cell shape properties and molecular component locations inside the cells. In the study of bacteria aging, the molecular components of interest are protein aggregates accumulated near bacteria boundaries. This particular location makes very ambiguous the correspondence between aggregates and cells, since computing accurately bacteria boundaries in phase-contrast time-lapse imaging is a challenging task. This paper proposes an active skeleton formulation for bacteria modelling which provides several advantages: an easy computation of shape properties (perimeter, length, thickness and orientation), an improved boundary accuracy in noisy images and a natural bacteria-centred coordinate system that permits the intrinsic location of molecular components inside the cell. Starting from an initial skeleton estimate, the medial axis of the bacterium is obtained by minimising an energy function which incorporates bacteria shape constraints. Experimental results on biological images and comparative evaluation of the performances validate the proposed approach for modelling cigar-shaped bacteria like Escherichia coli. The Image-J plugin of the proposed method can be found online at http://fluobactracker.inrialpes.fr. |
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Taylor & Francis Group |
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MILAB; |
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Admin @ si @JDM2017 |
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2784 |
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