首页> 外文会议>Visualization, Imaging, and Image Processing >EigenFIT: BUILDING PHOTOGRAPHIC QUALITY FACIAL COMPOSITES USING EVOLUTIONARY ALGORITHMS
【24h】

EigenFIT: BUILDING PHOTOGRAPHIC QUALITY FACIAL COMPOSITES USING EVOLUTIONARY ALGORITHMS

机译:EigenFIT:使用进化算法构建照相质量的面部复合材料

获取原文

摘要

A facial composite system is described for use in criminal investigations which has distinct advantages over current methods. Unlike traditional feature based methods, our approach uses both local and global facial models, allowing a witness to evolve plausible, photo-realistic face images in an intuitive way. The basic method combines random sampling from a facial appearance model (AM) with an evolutionary algorithm (EA) to drive the search procedure to convergence. Three variants of the evolutionary algorithm have been explored and their performance measured using a computer simulation of a human witness (virtual witness). Preliminary examples of composites generated with our system are presented which demonstrate the potential superiority of the evolutionary approach to composite generation.
机译:描述了一种用于犯罪调查的面部复合系统,其相对于当前方法具有明显的优势。与传统的基于特征的方法不同,我们的方法同时使用局部和全局面部模型,使证人可以直观地演变出真实,逼真的面部图像。基本方法将来自面部外观模型(AM)的随机采样与进化算法(EA)相结合,以驱动搜索过程收敛。已经探索了进化算法的三种变体,并使用人类见证人(虚拟见证人)的计算机模拟来测量其性能。给出了使用我们的系统生成的复合材料的初步示例,这些示例展示了进化方法对复合材料生成的潜在优势。

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