{"title":"Implementation of face detection algorithm based on KL-Gaussian Model on DSP","authors":"Hezhi Lin, Kunqing Wu, Xiangping Kong, Lianfeng Huang, Zhiyuan Shi, Siyan Chen","doi":"10.1109/ICASID.2012.6325324","DOIUrl":null,"url":null,"abstract":"Human face detection plays an important role in applications such as secure access, video surveillance. In view of the poor detection rate and low speed of the detection for faces in profile view, pose varied and complex background, this paper proposes the KL-Gaussian Model algorithm in YCbCr color space for face detection, which is designed and implemented on the TMS320DM6437 platform. Furthermore, to develop the DSP platform advantage, the optimization scheme for our designed face detection system is proposed. The result shows that the performance of the system is good with high detection rate and good robustness in the condition that faces with different poses and angles, which is significant to the intelligent development of video surveillance system.","PeriodicalId":408223,"journal":{"name":"Anti-counterfeiting, Security, and Identification","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anti-counterfeiting, Security, and Identification","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASID.2012.6325324","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Human face detection plays an important role in applications such as secure access, video surveillance. In view of the poor detection rate and low speed of the detection for faces in profile view, pose varied and complex background, this paper proposes the KL-Gaussian Model algorithm in YCbCr color space for face detection, which is designed and implemented on the TMS320DM6437 platform. Furthermore, to develop the DSP platform advantage, the optimization scheme for our designed face detection system is proposed. The result shows that the performance of the system is good with high detection rate and good robustness in the condition that faces with different poses and angles, which is significant to the intelligent development of video surveillance system.