首页> 外文会议>International Conference on Content-Based Multimedia Indexing >Cardio-Pulmonary Resuscitation (CPR) Scene Retrieval from Medical Simulation Videos Using Local Binary Patterns Over Three Orthogonal Planes
【24h】

Cardio-Pulmonary Resuscitation (CPR) Scene Retrieval from Medical Simulation Videos Using Local Binary Patterns Over Three Orthogonal Planes

机译:从医学模拟视频中使用三个正交平面上的局部二进制模式进行心肺复苏(CPR)场景检索

获取原文

摘要

We present a framework to detect and retrieve CPR activity scenes from medical simulation videos. Medical simulation is a modern training method for medical practitioners, where an emergency patient condition is simulated on humanlike mannequins and the students act upon. These simulation sessions are recorded for later debriefing. With the increasing number of simulation videos, automatic detection and retrieval of specific scenes became necessary. In this paper, we present an automated CPR scene retrieval system which can identify and retrieve CPR activity scenes, using Local Binary Patterns Over Three Orthogonal Planes (LBP-TOP) features. We present a comparative study of LBP-TOP features and Histogram of Orientation of Gradients (HOG3D) features for CPR action detection. We also present the results of decision level fusion of different classifier outputs. Promising classification results have been achieved, suggesting the proposed technique to be effective in detecting and retrieving CPR activity scenes from simulation videos.
机译:我们提供了一个从医学模拟视频中检测和检索CPR活动场景的框架。医学模拟是对医学从业者的一种现代培训方法,其中,在模拟人体的人体模型上模拟患者的紧急情况,然后学生采取行动。记录这些模拟会话以供以后汇报。随着模拟视频数量的增加,有必要对特定场景进行自动检测和检索。在本文中,我们提出了一种自动CPR场景检索系统,该系统可以使用三个正交平面(LBP-TOP)功能上的本地二进制模式来识别和检索CPR活动场景。我们目前进行的CBP动作检测的LBP-TOP特征和梯度方向直方图(HOG3D)特征的比较研究。我们还介绍了不同分类器输出的决策级融合结果。已经获得了有希望的分类结果,表明所提出的技术可以有效地从模拟视频中检测和检索CPR活动场景。

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