Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/15080
Título: Multi-Sensor people counting
Autores/as: Hernandez-Sosa, Daniel 
Castrillón-Santana, Modesto 
Lorenzo-Navarro, Javier 
Clasificación UNESCO: 120304 Inteligencia artificial
Palabras clave: People counting
EKF
MHI
Laser sensors
Fecha de publicación: 2011
Publicación seriada: Lecture Notes in Computer Science 
Conferencia: 5th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA) 
5th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2011 
Resumen: An accurate estimation of the number of people entering / leaving a controlled area is an interesting capability for automatic surveil- lance systems. Potential applications where this technology can be ap- plied include those related to security, safety, energy saving or fraud control. In this paper we present a novel con guration of a multi-sensor system combining both visual and range data specially suited for trou- blesome scenarios such as public transportation. The approach applies probabilistic estimation lters on raw sensor data to create intermediate level hypothesis that are later fused using a certainty-based integration stage. Promising results have been obtained in several tests performed on a realistic test bed scenario under variable lightning conditions.
URI: http://hdl.handle.net/10553/15080
ISBN: 9783642212567
ISSN: 0302-9743
DOI: 10.1007/978-3-642-21257-4_40
Fuente: Iberian Conference on Pattern Recognition and Image Analysis, ibPRIA 2011. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [ISSN 0302-9743], v. 6669 LNCS, p. 321-328
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