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Article

Real-Time Accumulative Computation Motion Detectors

1
Instituto de Investigación en Informática de Albacete, 02071-Albacete, Spain
2
Departamento de Sistemas Informáticos, Escuela de Ingenieros Industriales de Albacete, Universidad de Castilla-La Mancha, 02071-Albacete, Spain
3
Departamento de Sistemas Informáticos, Escuela Superior de Ingeniería Informática, Universidad de Castilla-La Mancha, 02071-Albacete, Spain
4
Department of Signal Theory and Communications, Escuela Politécnica Superior, Universidad de Alcalá, 28871-Alcalá de Henares, Madrid, Spain
*
Author to whom correspondence should be addressed.
Sensors 2009, 9(12), 10044-10065; https://doi.org/10.3390/s91210044
Received: 28 October 2009 / Revised: 24 November 2009 / Accepted: 30 November 2009 / Published: 10 December 2009
(This article belongs to the Special Issue Motion Detectors)
The neurally inspired accumulative computation (AC) method and its application to motion detection have been introduced in the past years. This paper revisits the fact that many researchers have explored the relationship between neural networks and finite state machines. Indeed, finite state machines constitute the best characterized computational model, whereas artificial neural networks have become a very successful tool for modeling and problem solving. The article shows how to reach real-time performance after using a model described as a finite state machine. This paper introduces two steps towards that direction: (a) A simplification of the general AC method is performed by formally transforming it into a finite state machine. (b) A hardware implementation in FPGA of such a designed AC module, as well as an 8-AC motion detector, providing promising performance results. We also offer two case studies of the use of AC motion detectors in surveillance applications, namely infrared-based people segmentation and color-based people tracking, respectively. View Full-Text
Keywords: accumulative computation; finite state automata; real-time; motion detection accumulative computation; finite state automata; real-time; motion detection
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MDPI and ACS Style

Fernández-Caballero, A.; López, M.T.; Castillo, J.C.; Maldonado-Bascón, S. Real-Time Accumulative Computation Motion Detectors. Sensors 2009, 9, 10044-10065. https://doi.org/10.3390/s91210044

AMA Style

Fernández-Caballero A, López MT, Castillo JC, Maldonado-Bascón S. Real-Time Accumulative Computation Motion Detectors. Sensors. 2009; 9(12):10044-10065. https://doi.org/10.3390/s91210044

Chicago/Turabian Style

Fernández-Caballero, Antonio, María Teresa López, José Carlos Castillo, and Saturnino Maldonado-Bascón. 2009. "Real-Time Accumulative Computation Motion Detectors" Sensors 9, no. 12: 10044-10065. https://doi.org/10.3390/s91210044

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