...
首页> 外文期刊>Pattern recognition letters >Fusing cluster-centric feature similarities for face recognition in video sequences
【24h】

Fusing cluster-centric feature similarities for face recognition in video sequences

机译:融合以聚类为中心的特征相似性以进行视频序列中的人脸识别

获取原文
获取原文并翻译 | 示例
           

摘要

The emergence of video has presented new challenges to the problem of face recognition. Most of the existing methods are focused towards the use of either representative exemplars or image sets to summarize videos. There is little work as to how they can be combined effectively to harness their individual strengths. In this paper, we investigate a new dual-feature approach to face recognition in video sequences that unifies feature similarities derived within local appearance-based clusters. Relevant similarity matching involving exemplar points and cluster subspaces are comprehensively modeled within a Bayesian maximum-a posteriori (MAP) classification framework. An extensive performance evaluation of the proposed method on three face video datasets have demonstrated promising results.
机译:视频的出现为面部识别问题提出了新的挑战。现有的大多数方法都集中于使用代表性示例或图像集来汇总视频。关于如何有效地组合它们以利用各自的优势,几乎没有任何工作。在本文中,我们研究了一种新的双重特征的视频序列人脸识别方法,该方法统一了基于局部外观的聚类中派生的特征相似性。在贝叶斯最大后验(MAP)分类框架内,对涉及示例点和聚类子空间的相关相似性匹配进行了全面建模。在三个面部视频数据集上对所提出的方法进行了广泛的性能评估,结果显示了令人鼓舞的结果。

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