Time filter

Source Type

Prague, Czech Republic

Cintula P.,Academy of Sciences of the Czech Republic | Klement E.P.,Johannes Kepler University | Mesiar R.,Slovak University of Technology in Bratislava | Mesiar R.,University of Ostrava | Navara M.,Center for Machine Perception
Fuzzy Sets and Systems

This paper surveys the present state of knowledge on propositional fuzzy logics extending SBL with an additional involutive negation. The involutive negation is added as a new propositional connective in order to improve the expressive power of the standard mathematical fuzzy logics based on continuous triangular norms. © 2009 Elsevier B.V. All rights reserved. Source

Navara M.,Center for Machine Perception | Petrik M.,University of Ostrava | Petrik M.,Academy of Sciences of the Czech Republic | Sarkoci P.,Slovak University of Technology in Bratislava
Proceedings of The International Symposium on Multiple-Valued Logic

The paper shows a direct correspondence between the first partial derivatives of a continuous Archimedean triangular norm and the first derivatives of its additive generator. An explicit formula for the additive generator is obtained. Application of the result is demonstrated on the problem of convex combinations of strict triangular norms. © 2010 IEEE. Source

Cech J.,Center for Machine Perception | Mittal R.,French Institute for Research in Computer Science and Automation | Deleforge A.,French Institute for Research in Computer Science and Automation | Sanchez-Riera J.,French Institute for Research in Computer Science and Automation | And 2 more authors.
IEEE-RAS International Conference on Humanoid Robots

In this paper we present a method for detecting and localizing an active speaker, i.e., a speaker that emits a sound, through the fusion between visual reconstruction with a stereoscopic camera pair and sound-source localization with several microphones. Both the cameras and the microphones are embedded into the head of a humanoid robot. The proposed statistical fusion model associates 3D faces of potential speakers with 2D sound directions. The paper has two contributions: (i) a method that discretizes the two-dimensional space of all possible sound directions and that accumulates evidence for each direction by estimating the time difference of arrival (TDOA) over all the microphone pairs, such that all the microphones are used simultaneously and symmetrically and (ii) an audio-visual alignment method that maps 3D visual features onto 2D sound directions and onto TDOAs between microphone pairs. This allows to implicitly represent both sensing modalities into a common audiovisual coordinate frame. Using simulated as well as real data, we quantitatively assess the robustness of the method against noise and reverberations, and we compare it with several other methods. Finally, we describe a real-time implementation using the proposed technique and with a humanoid head embedding four microphones and two cameras: this enables natural human-robot interactive behavior. © 2013 IEEE. Source

Simanek J.,Czech Technical University | Reinstein M.,Center for Machine Perception | Kubelka V.,Center for Machine Perception
IEEE/ASME Transactions on Mechatronics

This paper presents evaluation of four different state estimation architectures exploiting the extended Kalman filter (EKF) for 6-DOF dead reckoning of a mobile robot. The EKF is a well proven and commonly used technique for fusion of inertial data and robot's odometry. However, different approaches to designing the architecture of the state estimator lead to different performance and computational demands. While seeking the best possible solution for the mobile robot, the nonlinear model and the error model are addressed, both with and without a complementary filter for attitude estimation. The performance is determined experimentally by means of precision of both indoor and outdoor navigation, including complex-structured environment such as stairs and rough terrain. According to the evaluation, the nonlinear model combined with the complementary filter is selected as a best candidate (reaching 0.8 m RMSE and average of 4% return position error (RPE) of distance driven) and implemented for real-time onboard processing during a rescue mission deployment. © 2014 IEEE. Source

Gronat P.,French Institute for Research in Computer Science and Automation | Gronat P.,Czech Technical University | Gronat P.,Center for Machine Perception | Obozinski G.,CNRS ENS Informatics Department | And 4 more authors.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

The aim of this work is to localize a query photograph by finding other images depicting the same place in a large geotagged image database. This is a challenging task due to changes in viewpoint, imaging conditions and the large size of the image database. The contribution of this work is two-fold. First, we cast the place recognition problem as a classification task and use the available geotags to train a classifier for each location in the database in a similar manner to per-exemplar SVMs in object recognition. Second, as only few positive training examples are available for each location, we propose a new approach to calibrate all the per-location SVM classifiers using only the negative examples. The calibration we propose relies on a significance measure essentially equivalent to the p-values classically used in statistical hypothesis testing. Experiments are performed on a database of 25,000 geotagged street view images of Pittsburgh and demonstrate improved place recognition accuracy of the proposed approach over the previous work. © 2013 IEEE. Source

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