AdaBoost-based sensor fusion for credibility assessment

Author

Alipour, Hamid ; Zeng, Daniel ; Derrick, Douglas C.

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Arizona, Tucson, AZ, USA

fYear

2012

fDate

11-14 June 2012

Firstpage

224

Lastpage

226

Abstract

Individual credibility assessment is an ever-growing requirement in different applications including border crossing, airport checkpoint screening, criminal investigations, etc. In this paper, we describe a heterogeneous sensor fusion algorithm based on the AdaBoost algorithm and a speech emotional recognition technique in order to develop an automatic noninvasive credibility assessment system. Our initial results based on two available sensors show a promising increase in the accuracy and performance of the system.

Keywords

behavioural sciences computing; emotion recognition; eye; feature extraction; learning (artificial intelligence); object tracking; sensor fusion; speech recognition; AdaBoost algorithm; AdaBoost-based sensor fusion; airport checkpoint screening; automatic noninvasive credibility assessment system; behavioral indicators; border crossing; criminal investigation; eye tracker sensor; feature extraction; heterogeneous sensor fusion algorithm; individual credibility assessment; physiological indicators; speech emotional recognition technique; Accuracy; Biomedical monitoring; Classification algorithms; Emotion recognition; Sensor fusion; Speech; Speech recognition; Adaboost; Credibility Assessment; Data fusion; Sensor Signal Integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligence and Security Informatics (ISI), 2012 IEEE International Conference on

Conference_Location

Arlington, VA

Print_ISBN

978-1-4673-2105-1

Type

conf

DOI

10.1109/ISI.2012.6284314

Filename

6284314