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基于DBSCAN聚类算法的异常轨迹检测
Alternative TitleTrajectory outlier detection based on DBSCAN clustering algorithm
周培培; 丁庆海; 罗海波; 侯幸林
Department光电信息技术研究室
Source Publication红外与激光工程
ISSN1007-2276
2017
Volume46Issue:5Pages:238-245
Indexed ByEI ; CSCD
EI Accession number20173304042260
CSCD IDCSCD:6000360
Contribution Rank1
Keyword时空异常轨迹检测 Vmdl分割准则 Dbscan聚类算法 二级检测算法
Abstract现有的异常轨迹检测算法往往侧重于检测轨迹的空域异常,忽略了对轨迹时域异常的检测,并且检测精确度不高,针对此类问题,提出了基于增强聚类的异常轨迹检测算法。首先,采用基于速度的最小描述长度(VMDL)准则把轨迹简化成有序线段;然后,使用改进的线段间的距离定义,基于DBSCAN算法把线段分为不同的类,以建模局部正常运动模式;最后,采用先检测空间异常性再检测时间异常性的二级检测算法,检测时空异常轨迹点。在多个测试集上的实验结果表明:该算法可以检测位置、角度、速度等三种时空异常轨迹点,相对于其他算法,明显提高了异常轨迹检测的精确度。
Other AbstractExisting traditional trajectory outlier detection algorithms always focus on spatial outliers and ignore temporal outliers, and the accuracy is relatively low. To solve these problems, a simple and effective approach based on enhanced clustering algorithm was proposed to detect spatio-temporal trajectory outliers. Firstly, each original trajectory was simplified into a set of sequential line segments with the velocity鄄based minimum description length (VMDL) partition principle. Secondly, the distance formula between line segments was improved to enhance the clustering performance. Using DBSCAN algorithm, the line segments were classified into different groups which could represent local normal behaviors. Thirdly, outliers were detected using two鄄level detection algorithm which first detected spatial outliers and then detected temporal outliers. Experimental results on multiple trajectory data sets demonstrate that the proposed algorithm could successfully detect three kinds of spatio-temporal outliers, position, angle and velocity. Compared with other methods, the precision and accuracy make great improvement.
Language中文
Citation statistics
Cited Times:1[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20770
Collection光电信息技术研究室
Corresponding Author周培培
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院大学
3.航天恒星科技有限公司
4.中国科学院光电信息处理重点实验室
Recommended Citation
GB/T 7714
周培培,丁庆海,罗海波,等. 基于DBSCAN聚类算法的异常轨迹检测[J]. 红外与激光工程,2017,46(5):238-245.
APA 周培培,丁庆海,罗海波,&侯幸林.(2017).基于DBSCAN聚类算法的异常轨迹检测.红外与激光工程,46(5),238-245.
MLA 周培培,et al."基于DBSCAN聚类算法的异常轨迹检测".红外与激光工程 46.5(2017):238-245.
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