• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>4th International Conference on Smart and Sustainable City >A pedestrian tracking algorithm based on background unrelated head detection
【24h】

A pedestrian tracking algorithm based on background unrelated head detection

机译：基于背景无关头部检测的行人跟踪算法

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

Aiming at the problem that pedestrian tracking algorithm is prone to target tracking error in complex background, this paper proposes a pedestrian tracking algorithm based on human head detection to adapt to pedestrian tracking in many complex scenes. Firstly, the foreground segmentation technique is used to extract the motion foreground quickly. In the Adaboost classifier, the human body negative sample is added, and the Haar-like feature is used to detect the head on the basis of the movement foreground. The target tracking chain is established by detecting the head Walking tracker. The experimental results show that the algorithm proposed in this paper reduces the false detection rate and missed detection rate of the head, and improves the robustness to pedestrian tracking in many complex scenes.
机译：针对复杂背景下行人跟踪算法容易产生目标跟踪误差的问题，提出一种基于人头检测的行人跟踪算法，以适应多种复杂场景下的行人跟踪。首先，利用前景分割技术快速提取运动前景。在Adaboost分类器中，添加了人体阴性样本，并基于运动前景使用了类似Haar的特征来检测头部。目标跟踪链是通过检测头部步行跟踪器来建立的。实验结果表明，本文提出的算法降低了头部的误检率和漏检率，提高了许多复杂场景下行人跟踪的鲁棒性。

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