Real-time multiclass object recognition system based on adaptive correlation filtering

Viridiana Contreras, Victor H. Diaz-Ramirez, Francisco J. Ramirez-Arias, Kenia Picos

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

A real-time system for multiclass object recognition is proposed. The system is able to identify and correctly classify several moving targets from an input scene by using a bank of adaptive correlation filters with complex constraints implemented on a graphics processing unit. The bank of filters is synthesized with the help of an iterative algorithm based on complex synthetic discriminant functions. At each iteration, the algorithm optimizes the discrimination capability of each filter in the bank by using all available information about the known patterns to be recognized and unwanted patterns to be rejected such as false objects or a background. Computer simulation results obtained with the proposed system in real and synthetic scenes are presented and discussed in terms of pattern recognition performance and real-time operation speed.

Idioma originalInglés
Título de la publicación alojadaOptics and Photonics for Information Processing VI
DOI
EstadoPublicada - 2012
EventoOptics and Photonics for Information Processing VI - San Diego, CA, Estados Unidos
Duración: 15 ago. 201216 ago. 2012

Serie de la publicación

NombreProceedings of SPIE - The International Society for Optical Engineering
Volumen8498
ISSN (versión impresa)0277-786X

Conferencia

ConferenciaOptics and Photonics for Information Processing VI
País/TerritorioEstados Unidos
CiudadSan Diego, CA
Período15/08/1216/08/12

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