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嵌入式人脸识别器的GUI设计 被引量:4
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作者 向征 马争鸣 《计算机工程与应用》 CSCD 2012年第14期79-83,共5页
Qt/embedded是图形化界面开发工具的嵌入式版本,整体采用面向对象编程,拥有较高的运行效率和良好的体系架构和编程模式。达芬奇技术是基于DSP的数字音视频优化的系统解决方案,它在嵌入式操作系统方面对Linux的支持极为完善,可以实现复杂... Qt/embedded是图形化界面开发工具的嵌入式版本,整体采用面向对象编程,拥有较高的运行效率和良好的体系架构和编程模式。达芬奇技术是基于DSP的数字音视频优化的系统解决方案,它在嵌入式操作系统方面对Linux的支持极为完善,可以实现复杂GUI系统的设计。利用qt/embedded和达芬奇技术完成了人脸识别器的图形用户界面设计,实现了人脸检测结果显示,人脸数据的修改和更新功能。另外成功实现了qt/em-bedded在DM6446上的移植,并有效使用了DM6446的视频处理前端和视频处理后端实现视频采集和显示。 展开更多
关键词 QT/EMBEDDED 达芬奇技术 图形用户界面 DM6446 人脸识别器
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A new discriminative sparse parameter classifier with iterative removal for face recognition
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作者 TANG De-yan ZHOU Si-wang +2 位作者 LUO Meng-ru CHEN Hao-wen TANG Hui 《Journal of Central South University》 SCIE EI CAS CSCD 2022年第4期1226-1238,共13页
Face recognition has been widely used and developed rapidly in recent years.The methods based on sparse representation have made great breakthroughs,and collaborative representation-based classification(CRC)is the typ... Face recognition has been widely used and developed rapidly in recent years.The methods based on sparse representation have made great breakthroughs,and collaborative representation-based classification(CRC)is the typical representative.However,CRC cannot distinguish similar samples well,leading to a wrong classification easily.As an improved method based on CRC,the two-phase test sample sparse representation(TPTSSR)removes the samples that make little contribution to the representation of the testing sample.Nevertheless,only one removal is not sufficient,since some useless samples may still be retained,along with some useful samples maybe being removed randomly.In this work,a novel classifier,called discriminative sparse parameter(DSP)classifier with iterative removal,is proposed for face recognition.The proposed DSP classifier utilizes sparse parameter to measure the representation ability of training samples straight-forward.Moreover,to avoid some useful samples being removed randomly with only one removal,DSP classifier removes most uncorrelated samples gradually with iterations.Extensive experiments on different typical poses,expressions and noisy face datasets are conducted to assess the performance of the proposed DSP classifier.The experimental results demonstrate that DSP classifier achieves a better recognition rate than the well-known SRC,CRC,RRC,RCR,SRMVS,RFSR and TPTSSR classifiers for face recognition in various situations. 展开更多
关键词 collaborative representation-based classification discriminative sparse parameter classifier face recognition iterative removal sparse representation two-phase test sample sparse representation
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