Testanlagen
Roboter Test StreckeRoboter Test StreckeRoboter Test StreckeUnterwasser TestbedSpace Testbed
Projektkoordination
Vortragsrückblick

Vortragsdetails

Ort:DFKI Bremen
Robotics Innovation Center
Robert-Hooke-Str. 5
Konferenzraum 117
Opens internal link in current windowAnfahrtsbeschreibung
Dr. Asma Rabaoui,  LAGIS (Laboratory of Automatics, Data-processing & Signal) -Central School of Lille - France CIBER-BBN
Signal classification and estimation : Kernel based methods and Bayesian approaches drivers inattention through statistical shape models
(Abstract)
My talk will be centered on a range of topics in signal processing including mainly Kernel methods (Support Vector Machines) for sounds Classification and Bayesian methods for GNSS based localization.

The first part of my talk concerns the problem of sounds recognition for surveillance and security applications. A flexible approach based on one-class support vector machines (1-SVMs) was developed. The performance of this method was illustrated on an audio database characterized by its diversity. Our approach overperforms the conventional hidden Markov model-based system in the experiments conducted. Besides, we provided empirical results showing that the single-class SVM outperforms a combination of binary SVMs. Additional experiments demonstrated that our method is robust to environmental noise.

Recently, I was interested in Bayesian methods (Monte-Carlo and Sequential Monte Carlo Methods and Non Parametrical Bayesian Analysis). The application was Global Navigation Satellite Systems (GNSS) for vehicles localization. In real urban environment, in order to ensure high accuracy positioning a good estimation of the observation error was required. We addressed the case where the noise probability density functions are of unknown functional form. A flexible Bayesian nonparametric noise model based on Dirichlet Process Mixtures (DPM) was introduced. This novel approach was compared to a Jump Markov System (JMS) based on a finite Gaussian mixture modeling and some interesting validation schemes were conducted.