...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Earth Surface Dynamics >Automated quantification of floating wood pieces in rivers from video monitoring: a new software tool and validation
【24h】

Automated quantification of floating wood pieces in rivers from video monitoring: a new software tool and validation

机译：从视频监控自动化河流中浮动木屑的量化：新的软件工具和验证

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Wood is an essential component of rivers and plays a significant role in ecology and morphology. It can be also considered a risk factor in rivers due to its influence on erosion and flooding. Quantifying and characterizing wood fluxes in rivers during floods would improve our understanding of the key processes but are hindered by technical challenges. Among various techniques for monitoring wood in rivers, streamside videography is a powerful approach to quantify different characteristics of wood in rivers, but past research has employed a manual approach that has many limitations. In this work, we introduce new software for the automatic detection of wood pieces in rivers. We apply different image analysis techniques such as static and dynamic masks, object tracking, and object characterization to minimize false positive and missed detections. To assess the software performance, results are compared with manual detections of wood from the same videos, which was a time-consuming process. Key parameters that affect detection are assessed, including surface reflections, lighting conditions, flow discharge, wood position relative to the camera, and the length of wood pieces. Preliminary results had a 36?% rate of false positive detection, primarily due to light reflection and water waves, but post-processing reduced this rate to 15?%. The missed detection rate was 71?% of piece numbers in the preliminary result, but post-processing reduced this error to only 6.5?% of piece numbers and 13.5?% of volume. The high precision of the software shows that it can be used to massively increase the quantity of wood flux data in rivers around the world, potentially in real time. The significant impact of post-processing indicates that it is necessary to train the software in various situations (location, time span, weather conditions) to ensure reliable results. Manual wood detections and annotations for this work took over 150 labor hours. In comparison, the presented software coupled with an appropriate post-processing step performed the same task in real time (55?h) on a standard desktop computer.
机译：木材是河流的重要组成部分，在生态和形态中起着重要作用。由于其对侵蚀和洪水的影响，它也可以考虑河流的危险因素。在洪水期间量化和表征河流中的木质势态会改善我们对关键过程的理解，但受到技术挑战的阻碍。在河流中监测木材的各种技术中，StreamSed视频操作是一种强大的方法，可以量化河流中木材的不同特征，但过去的研究采用了具有许多限制的手动方法。在这项工作中，我们介绍了新软件，用于在河流中自动检测木片。我们应用不同的图像分析技术，例如静态和动态掩模，对象跟踪和对象表征，以最小化误报和错过的检测。为了评估软件性能，将结果与来自同一视频的手工检测相比，这是一个耗时的过程。评估影响检测的关键参数，包括表面反射，照明条件，流量放电，相对于相机的木材位置，以及木材的长度。初步结果具有36？％的假阳性检测率，主要是由于光反射和水波，但后处理降低了该速率为15？％。错过的检出率为初步结果中的71倍，但后处理将该误差减少到仅6.5？％的块数和13.5？％的体积。软件的高精度表明，它可以用于大规模增加世界周围的木磁通数据量，可能实时地。后处理的重大影响表明有必要在各种情况下培训软件（位置，时间跨度，天气条件），以确保可靠的结果。这项工作的手动木材检测和注释花了150多个劳动力。相比之下，所提出的软件与适当的后处理步骤耦合，在标准桌面计算机上实时（55ΩH）执行相同的任务。

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