• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>SIBGRAPI Conference on Graphics, Patterns and Images >Single Sample Face Recognition from Video via Stacked Supervised Auto-Encoder
【24h】

Single Sample Face Recognition from Video via Stacked Supervised Auto-Encoder

机译：通过堆叠的有监督自动编码器从视频中对单个样本人脸进行识别

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This work proposes and evaluates strategies based on Stacked Supervised Auto-Encoders (SSAE) for face representation in video surveillance applications. The study focuses on the identification task with a single sample per person (SSPP) in the gallery. Variations in terms of pose, facial expression, illumination and occlusion are approached in two ways. First, the SSAE extracts features from face images, which are robust to such variations. Second, we propose methods to exploit the multiple samples per persons probes (MSPPP) that can be extracted from video sequences. Three variants of the proposed method are compared upon HONDA/UCSD and VIDTIMIT video datasets. The experimental results demonstrate that strategies combining SSAE and MSPPP are able to outperform other SSPP methods, such a local binary patterns, in face recognition from video.
机译：这项工作提出并评估了基于堆叠监督自动编码器（SSAE）的视频监控应用中的人脸表示策略。该研究着重于识别任务，并在画廊中使用每人一个样本（SSPP）。姿势，面部表情，照度和遮挡方面的变化可以通过两种方法来解决。首先，SSAE从面部图像中提取特征，这些特征对于此类变化具有鲁棒性。其次，我们提出了利用可从视频序列中提取的每人多个样本探针（MSPPP）的方法。在HONDA / UCSD和VIDTIMIT视频数据集上比较了所提出方法的三种变体。实验结果表明，结合SSAE和MSPPP的策略在视频人脸识别方面能够胜过其他SSPP方法，例如局部二进制模式。

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