Research On Parallel Computing Of Face Dection Based On Epiphany Multicore Processor

The object monitoring and identification based on image processing have been the key research topics in the field of computer vision.Face is the basis for human identity verification,which is one of the main characteristics of human identification.Meanwhile,face detection has become a new human-computer interaction technology and widely used in monitoring system,image retrieval and other aspects.Now,the most commonly used face detection method is Ada Boost algorithm,which ensures the efficiency and accuracy of detection.The research of face detection has been focused on designing new algorithms or improving the accuracy of existing methods.However,due to the limited resources of embedded devices,the existing face detection methods are inefficient in embedded devices.Therefore,the efficiency of face detection has become the key problem of face detection.To solve this problem,this paper realizes the parallel computing of face detection.Based on the Parallella platform,the AdaBoost based face detection algorithm is processed in parallel with the cluster and the Epiphany multicore processor,and the parallel processing system for face detection is designed.This paper takes the studies from the following aspects.Firstly,this paper points out the defect in face detection process,which is the scanning window occupies a great deal of system resources,and proposes a multicore parallel face detection method.Secondly,considering the detection task of each frame is similar as the resolution of each frame in the video is same,so this paper process the same part of the single frame image detection only once to optimize the parallel face detection system and improve system performance.Thirdly,using MPI technology to extend the parallel face detection of single board to the cluster,and improve the computing speed by deploying the cluster.Each of the boards in the cluster uses the multicore processor for parallel computation.Finally,this paper uses the Parallella platform to realize the parallel face detection system.The Parallella platform includes ZYNQ and multicore processor,the ARM A9 processor running the face detection system in ZYNQ and multicore processors help ARM deal with complex computations and the performance of the parallel computing system based on Parallella platform is verified.