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A new change detection method and its application to epilepsy monitoring video

机译:一种新的变化检测方法及其在癫痫监测视频中的应用

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Video recording is often conducted during epilepsy monitoring. This video provides important information correlating electrical activity with a patient's behavior during a seizure. Change detection in this type of video provides a tool to detect the motion of the patient to aid in diagnosis. Traditional methods detect changes by testing variations between frame pairs. Although effective in common applications, these methods are not satisfactory in detecting movements in medical video involving small local motion. In this work, we present a new change detection method by utilizing multiple video frames. Temporal domain properties are explored to warrant more robustness in the detection of small changes. The effectiveness of the new method is demonstrated by experimental results.
机译:通常在癫痫监测期间进行视频记录。该视频提供了重要信息,使癫痫发作期间的电活动与患者的行为相关。这种类型的视频中的变化检测提供了一种检测患者运动的工具,以帮助诊断。传统方法通过测试帧对之间的变化来检测变化。尽管在常见应用中有效,但是这些方法在检测涉及小的局部运动的医学视频中的运动方面并不令人满意。在这项工作中,我们提出了一种利用多个视频帧的新变化检测方法。探索时域属性以确保在检测微小变化时具有更高的鲁棒性。实验结果证明了该新方法的有效性。

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