• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE 10th International Conference on Ubiquitous Intelligence and Computing; IEEE 10th International Conference on Autonomic and Trusted Computing >An Automatic Face Annotation System Featuring High Accuracy for Online Social Networks
【24h】

An Automatic Face Annotation System Featuring High Accuracy for Online Social Networks

机译：在线社交网络的高精度人脸自动标注系统

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The development of fully automatic face annotation techniques in online social networks (OSNs) is currently very important for effective management and organization of the large numbers of personal photos shared on social network platforms. In this paper, we construct the personalized and adaptive Fused Face Recognition unit for each member, which uses the Adaboost algorithm to fuse several different types of base classifiers to produce highly reliable face annotation results. The experiment results demonstrate that our proposed approach achieves a significantly higher level of efficacy, outperforming other state-of-the-art face annotation methods for real-life personal photos featuring pose variations. Our evaluation methodologies produced respective F-measure and Similarity accuracy rates that were 57.99% and 54.23% higher for the proposed method in comparison to other tested methods.
机译：当前，在线社交网络（OSN）中全自动面部注释技术的发展对于有效管理和组织在社交网络平台上共享的大量个人照片非常重要。在本文中，我们为每个成员构造了个性化的自适应融合人脸识别单元，该单元使用Adaboost算法融合几种不同类型的基础分类器以产生高度可靠的人脸注释结果。实验结果表明，我们提出的方法可达到更高的功效水平，优于其他具有姿势变化的现实生活中个人照片的其他最先进的面部注释方法。与其他测试方法相比，我们的评估方法得出的F度量和相似度准确率分别比拟议方法高57.99％和54.23％。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号