Computer Science ›› 2015, Vol. 42 ›› Issue (3): 266-270.doi: 10.11896/j.issn.1002-137X.2015.03.055

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Fast Video Detection Scheme Based on Multi-core Processor and GPU

YANG Juan, ZENG Miao-xiang, XU Jing and XU Wei   

  • Online:2018-11-14 Published:2018-11-14

Abstract: At present,the speed of video detection based on general structure is very slow,and it is difficult to meet the requirement of real-time network video monitoring.This paper showed a new video detection method based on multi-core processor and graphic processing unit (GPU).This method uses multi-core processor to realize video decoding,and uses the GPU to realize the SURF (Speed Up Robust Features) and SVM (Support Vector Machines) algorithm to detect the image.Compared with video detection scheme based on general PC architecture,the performance of the method based on multi-core processor and GPU can be improved over 10 times.

Key words: Video detect,Multi-core processor,GPU,SURF,SVM

[1] Zhao G,Wang S,Wang T,et al.HSV color space and face detec-tion based objectionable image detecting[C]∥2008 Second International Conference on Future Generation Communication and Networking Symposia.2008,3:107-110
[2] Yu J J,Han S W.Skin detection for adult image identification[C]∥2014 16th International Conference on Advanced Communication Technology (ICACT).IEEE,2014:645-648
[3] Lee H,Lee S,Nam T.Implementation of high performance objectionable video classification system[C]∥The 8th International Conference Advanced Communication Technology,2006(ICACT 2006).IEEE,2006,2:4-962
[4] Kim C Y,Kwon O J,Kim W G,et al.Automatic system for filtering obscene video[C]∥10th International Conference on Advanced Communication Technology,2008(ICACT 2008).IEEE,2008,2:1435-1438
[5] Yu W,Qu Z,Jin Y.A Pornographic Video Detection MethodBased on Semi-supervised Learning on Graphs[C]∥2013 Sixth International Symposium on Computational Intelligence and Design (ISCID).IEEE,2013,2:347-350
[6] Ochoa V M T,Yayilgan S Y,Cheikh F A.Adult video content detection using Machine Learning Technology[C]∥2012 Eighth International Conference on Signal Image Technology and Internet Based System(SITIS).2012:967-974
[7] Esmaeili M M,Fatourechi M,Ward R K.A robust and fast video copy detection system using content-based fingerprinting[J].IEEE Transactions on Information Forensics and Security,2011,6(1):213-226
[8] Endeshaw T,Garcia J,Jakobsson A.Classification of indecentvideos by low complexity repetitive motion detection[C]∥37th IEEE Applied Imagery Pattern Recognition Workshop,2008(AIPR’08).IEEE,2008:1-7
[9] Wu J,Wang C F.Fast computation of cylindrical Green’s functions with graphic processing unit[C]∥Antennas and Propagation Society International Symposium (APSURSI).2013:1884-1885
[10] Mirollo A C,Guerrero J J,Sagues C.SURF features for efficient robot localization with omnidirectional image[C]∥2007 IEEE International Conference on Robotics and Automation.2007:3901-3907
[11] Szczuko P.Influence of image transformations and quality degradations on SURF detector efficiency[C]∥Signal Processing:Algorithms,Architectures,Arrangements,and Applications (SPA),2013.IEEE,2013:285-290

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