Accelerating bioinspired lateral interaction in accumulative computation for real-time moving object detection with graphics processing units |
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Authors: | Sánchez José L. López María T. Pastor José Manuel Delgado Ana E. Fernández-Caballero Antonio |
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Affiliation: | 1.Departamento de Sistemas Informáticos, Universidad de Castilla-La Mancha, Albacete, Spain ;2.Departamento de Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Madrid, Spain ; |
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Abstract: | Biologically-inspired computer vision is a research area that offers prominent directions in a large variety of fields. Several processing algorithms inspired in natural vision enable detecting moving objects from video sequences so far. One example is lateral interaction in accumulative computation (LIAC), a classical bioinspired method that has been applied to numerous environments and applications. LIAC is the implementation for computer vision of two biologically-inspired methods denominated algorithmic lateral interaction and accumulative computation. The method has traditionally reached high precision but unfortunately requires high computing times. This paper introduces a proposal based on graphics processing units in order to speed up the original sequential code. This way not only excellent performance in terms of accuracy is maintained, but also real-time is obtained. A speed-up of 67× from the parallel over its sequential counterpart is achieved for several tested video sequences. |
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