...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The international arab journal of information technology >An Improved Statistical Model of Appearance under Partial Occlusion
【24h】

An Improved Statistical Model of Appearance under Partial Occlusion

机译：部分遮挡下外观的改进统计模型

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 Appearance Models (AMs) are widely used in many applications related to face recognition, expression analysis and computer vision. Despite its popularity, the AMs are not much more accurate due to partial occlusion. Therefore, the authors have developed Robust Normalization Inverse Compositional Image Alignment (RNICIA) algorithm to solve partial occlusion problem. However, the RNICIA algorithm is not efficient due to high complexity and un-effective due to poor selection of Robust Error Function and scale parameter that depends on a particular training dataset. In this paper, an Improved Statistical Model of Appearance (ISMA) method is proposed by integration techniques of perceptual-oriented uniform Color Appearance Model (CAM) and Jensen-Shannon Divergence (JSD) to overcome these limitations. To reduce iteration steps which decrease computational complexity, the distribution of probability of each occluded and un-occluded image regions is measured. The ISMA method is tested by using convergence measure on 600 facial images by varying degree of occlusion from 10% to 50%. The experimental results indicate that the ISMA method is achieved more than 95% convergence compared to RNICIA algorithm thus the performance of appearance models have significantly improved in terms of partial occlusion.
机译：外观模型（AMs）广泛用于与人脸识别，表情分析和计算机视觉有关的许多应用程序中。尽管很受欢迎，但由于部分遮挡，AM并没有准确得多。因此，作者开发了鲁棒归一化逆合成图像对齐（RNICIA）算法来解决部分遮挡问题。但是，由于复杂性高，RNICIA算法效率不高；由于依赖特定训练数据集的鲁棒误差函数和比例参数选择不当，因此RNICIA算法无效。为了克服这些局限性，本文提出了一种面向感知的统一颜色外观模型（CAM）和Jensen-Shannon Divergence（JSD）集成技术，提出了一种改进的统计外观模型（ISMA）方法。为了减少降低计算复杂度的迭代步骤，测量每个被遮挡和未被遮挡的图像区域的概率的分布。通过对10张到50％的遮挡程度的600张面部图像进行收敛测量，对ISMA方法进行了测试。实验结果表明，与RNICIA算法相比，ISMA方法的收敛率超过95％，因此外观模型的性能在部分遮挡方面得到了显着改善。

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