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提高从新生儿癫痫发作视频记录中提取颞部运动活动信号所使用的运动跟踪方法的准确性和可靠性。

Improving the accuracy and reliability of motion tracking methods used for extracting temporal motor activity signals from video recordings of neonatal seizures.

作者信息

Karayiannis Nicolaos B, Xiong Yaohua, Frost James D, Wise Merrill S, Mizrahi Eli M

机构信息

Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204-4005, USA.

出版信息

IEEE Trans Biomed Eng. 2005 Apr;52(4):747-9. doi: 10.1109/TBME.2005.844047.

Abstract

This paper presents an approach for improving the accuracy and reliability of motion tracking methods developed for video based on block motion models. This approach estimates the displacement of a block of pixels between two successive frames by minimizing an error function defined in terms of the pixel intensities at these frames. The minimization problem is made analytically tractable by approximating the error function using a second-order Taylor expansion. The improved reliability of the proposed method is illustrated by its application in the extraction of temporal motor activity signals from video recordings of neonatal seizures.

摘要

本文提出了一种方法,用于提高基于块运动模型开发的视频运动跟踪方法的准确性和可靠性。该方法通过最小化根据这些帧处的像素强度定义的误差函数,来估计两个连续帧之间的像素块位移。通过使用二阶泰勒展开近似误差函数,使最小化问题在解析上易于处理。所提出方法的更高可靠性通过其在从新生儿癫痫视频记录中提取时间性运动活动信号中的应用得到了说明。

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