• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of electronic imaging >Real-time unmanned aerial vehicle tracking of fast moving small target on ground
【24h】

Real-time unmanned aerial vehicle tracking of fast moving small target on ground

机译：地面快速移动小目标的实时无人机跟踪

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

To solve the problems of occlusion and fast motion of small targets in unmanned aerial vehicle target tracking, an adaptive algorithm that fuses the improved color histogram tracking response and the correlation filter tracking response based on multichannel histogram of oriented gradient features is proposed to realize small target tracking with high accuracy. The state judgment index is used to determine whether the target is in a fast motion or an occlusion state. In the fast motion state, the search area is enlarged, and the color optimal model that suppresses the suspected area is used for rough detection. Then, redetection in the location of multiple peaks in the rough detection response is carried out using the correlation filter to accurately locate the target. In an occlusion state, the model stops updating, the search area is expanded, and the current color model is used for rough detection. Then, redetection in the place of multiple peaks in the rough detection response is carried out using the correlation filter to accurately locate the target. Experimental results show that the proposed method can track small targets accurately. The frame rate of the proposed method is 40.23 frames/s, indicating usable real-time performance. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.
机译：为解决无人机目标跟踪中小目标的遮挡和快速运动的问题，提出了一种自适应算法，该算法融合了改进的彩色直方图跟踪响应和基于定向梯度特征的多通道直方图的相关滤波器跟踪响应，以实现小目标跟踪精度高。状态判断指标用于确定目标是处于快速运动还是处于遮挡状态。在快动作状态下，搜索区域被扩大，并且抑制可疑区域的色彩最佳模型被用于粗略检测。然后，使用相关滤波器对粗略检测响应中多个峰的位置进行重新检测，以准确定位目标。在遮挡状态下，模型停止更新，搜索区域被扩展，当前颜色模型用于粗略检测。然后，使用相关滤波器对粗略检测响应中的多个峰值进行重新检测，以准确定位目标。实验结果表明，该方法可以准确地跟踪小目标。所提出方法的帧速率为40.23帧/秒，表明可用的实时性能。 （C）作者。由SPIE根据Creative Commons Attribution 3.0 Unported License发布。

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