HEAD DETECTION INSIDE VEHICLES WITH A MODIFIED SVM FOR SAFER AIRBAGS
This paper proposes a vision system for detecting and localizing a passenger's head within the cockpit of a vehicle. A monocular camera is used to detect the passenger's head and to give its 2D position to the detection system. A had detection algorithm is based on a modified version of one of the most recent neural network methods known as Support Vector Machines (SVM). 3D information is then used to give the exact position of the passenger's head. The information regarding the presence of a person in the passenger seat and the position of their head is then used to control the deployment of the passenger airbag.
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Supplemental Notes:
- Publication Date: 2001. IEEE Service Center, Piscataway NJ
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Corporate Authors:
Siemens Aktiengesellschaft
Machtfinger Strasse 10, Postfach 100079
8000 Munich, GermanyTexas A&M University, College Station
Department of Mechanical Engineering
College Station, TX United States 77843-3123National Science Foundation
1800 G Street, NW
Washington, DC United States 20550University of California, Berkeley
California PATH Program, Institute of Transportation Studies
Richmond Field Station, 1357 South 46th Street
Richmond, CA United States 94804-4648Universidad Nacional Autonoma de Mexico. Instituto de Ingenieria
,University of California, Berkeley
Department of Mechanical Engineering
Berkeley, CA United States 94720-1740DaimlerChrysler Forschungszentrum in Ulm
,Technische Universitat Munchen. Fachgebiet Verkehrsplanung und Verkehrsplanung
,University of California, Irvine
Institute of Transportation Studies
4000 Anteater Instruction and Research Building
Irvine, CA United States 92697Nanyang Technological University
Centre for High Performance Embedded Systems
Singapore, Singapore -
Authors:
- Reyna, Roberto
- Giralt, Alain
- Esteve, Daniel
- Conference:
- Publication Date: 2001
Language
- English
Media Info
- Pagination: p. 268-272
Subject/Index Terms
- TRT Terms: Air bags; Driver monitoring; Image processing
- Subject Areas: Safety and Human Factors;
Filing Info
- Accession Number: 00963574
- Record Type: Publication
- Source Agency: UC Berkeley Transportation Library
- Files: PATH
- Created Date: Oct 2 2003 12:00AM