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计算机系统应用英文版:2014,23(5):89-94
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应用Log-协方差矩阵距离的实验鼠行为分类方法
(淮北师范大学 计算机科学与技术学院, 淮北 235000)
Classifying Algorithm of Mouse Behavior Using Distance of Log-covariance Matrix
(School of Computer and Technology, Huaibei Normal University, Huaibei 235000, China)
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Received:September 13, 2013    Revised:October 28, 2013
中文摘要: 实验鼠行为分类在神经科学、生物科学、药物开发等领域的研究中十分重要. 针对行为分析中实验鼠肢体短小,提取相关信息困难问题,应用实验鼠轮廓抽取特征,进行实验鼠的行为分类. 首先从视频每一帧图像中分割出实验鼠轮廓,并提取轮廓中心从八个方向上到轮廓边缘的距离以及轮廓区域的两个主分量,组成一个10维向量作为特征向量,最后应用协方差距离进行分类. 实验结果显示,分类正确率达87.6%.
中文关键词: 实验鼠  轮廓  特征值  协方差距离  行为分类
Abstract:The classification of mice behavior is very important in the study fields of neuroscience, biological science, drug development and so on. In behavioral analysis,according to the short limbs of mice, it is difficult to extract relevant information. Mouse behavior is classified using characteristics of mouse contour. Firstly, mouse contour is extracted from each frame behavior video. Then, the distance of eight directions are calculated which are from contour center to edge and calculate two main components of contour. Using these values to form ten dimensional vectors as feature vector. Finally, calculate the log-covariance distance and classify. Experimental results show that the correct rate of classification is 87.6%.
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马玲玲,洪留荣,胡倩.应用Log-协方差矩阵距离的实验鼠行为分类方法.计算机系统应用,2014,23(5):89-94
MA Ling-Ling,HONG Liu-Rong,HU Qian.Classifying Algorithm of Mouse Behavior Using Distance of Log-covariance Matrix.COMPUTER SYSTEMS APPLICATIONS,2014,23(5):89-94