Localization of Passengers Inside Intelligent Vehicles by the Use of Ultra Wideband Radars
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Standard
Signal processing, image processing and pattern recognition: international conference, SIP 2011. ed. / Tai-hoon Kim; Hojjat Adeli; Carlos Ramos; Byeong-Ho Kang. Springer, 2011. p. 92-102 (Communications in Computer and Information Science; Vol. 260 CCIS).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Harvard
APA
Vancouver
Bibtex
}
RIS
TY - CHAP
T1 - Localization of Passengers Inside Intelligent Vehicles by the Use of Ultra Wideband Radars
AU - Galdia, Philipp
AU - Carsten, Koch
AU - Georgiadis, Anthimos
PY - 2011
Y1 - 2011
N2 - In this paper an approach for the localization of passengers inside a vehicle by the use of ultra wideband technology (UWB) is presented. Established approaches as static background subtraction for the separation of fore- and background show good performance in static scenes. But in the case of a dynamic surrounding such as a car’s interior, former techniques are limited, since significant errors are produced as soon as the scene gets dynamic.Instead of trying to separate fore- and background, the presented approach involves the complete data set in a first step. Since human breathing shows certain behaviour such as a typical frequency and amplitude, the breathing movement can be separated from other movement or static parts of the radar scan. The respiration and by that the passenger inside a vehicle is located and tracked.
AB - In this paper an approach for the localization of passengers inside a vehicle by the use of ultra wideband technology (UWB) is presented. Established approaches as static background subtraction for the separation of fore- and background show good performance in static scenes. But in the case of a dynamic surrounding such as a car’s interior, former techniques are limited, since significant errors are produced as soon as the scene gets dynamic.Instead of trying to separate fore- and background, the presented approach involves the complete data set in a first step. Since human breathing shows certain behaviour such as a typical frequency and amplitude, the breathing movement can be separated from other movement or static parts of the radar scan. The respiration and by that the passenger inside a vehicle is located and tracked.
KW - Engineering
KW - airbag
KW - localization
KW - radar
KW - Ultra wideband
KW - vital sign analysis
UR - http://www.scopus.com/inward/record.url?scp=84855404321&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-27183-0_11
DO - 10.1007/978-3-642-27183-0_11
M3 - Article in conference proceedings
SN - 3-642-27183-0
T3 - Communications in Computer and Information Science
SP - 92
EP - 102
BT - Signal processing, image processing and pattern recognition
A2 - Kim, Tai-hoon
A2 - Adeli, Hojjat
A2 - Ramos, Carlos
A2 - Kang, Byeong-Ho
PB - Springer
T2 - 2nd European symposium of the Societal Impact of Pain - SIP 2011
Y2 - 8 December 2011 through 10 December 2011
ER -