首页> 外文期刊>Computer vision and image understanding >A resample strategy and artificial bee colony optimization-based 3d range imaging registration
【24h】

A resample strategy and artificial bee colony optimization-based 3d range imaging registration

机译:重采样策略和基于人工蜂群优化的3d范围成像配准

获取原文
获取原文并翻译 | 示例
           

摘要

For two point clouds with low overlapping rate, the registration process is more difficult and the registration speed is slow. In this paper, we reduce the number of sampling points to simplify the calculation, and then propose a new idea based on equal interval method called resample strategy, it can effectively avoid ambiguity during the registration process by improving the ergodicity and utilization of the sampling point set. In addition, we also introduce a new solution search equation that has more exploitation performance to alternatively search with an enhanced artificial bee colony algorithm. The computation time has been effectively reduced by using these two proposed strategies. The registration experimental results aiming to a variety of point cloud models show that our 3d image registration algorithm is better than many other algorithms based on classical or improved bionic intelligence optimization methods.
机译:对于重叠率低的两点云,配准过程较困难,配准速度较慢。本文通过减少采样点数来简化计算,然后提出了一种基于等间隔方法的重新采样策略,通过提高采样点的遍历性和利用率可以有效避免配准过程中的歧义。组。此外,我们还引入了一种新的解决方案搜索方程,该方程具有更高的开发性能,可以使用增强的人工蜂群算法进行替代搜索。通过使用这两种建议的策略,有效地减少了计算时间。针对各种点云模型的配准实验结果表明,我们的3d图像配准算法优于许多基于经典或改进的仿生智能优化方法的其他算法。

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