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영어

This paper proposes a method for optimizing and parallelizing a pedestrian detection algorithm based on CENTRIST in the embedded environment. Pedestrian detection is applied to various areas, but there is a difficulty in the real-time processing of pedestrian detection in the embedded environment. In this paper, a pedestrian detection algorithm that has improved performance by reducing unnecessary memory access due to duplicate computations for real-time processing. The proposed algorithm was implemented in the ALDEBARAN embedded processor(300MHz) which can perform parallel processing. For efficient parallel processing, images were divided into halves which were then processed separately in two CPU cores and the volume of computations was balanced between the two CPU cores. For input images, 512x360 sized images were used. The single core showed the performance of 3.1 frames per second. In the dual core for which the wait time in the process of parallelizing was reduced, the performance improved by about 55% to 4.8 frames per second.