CAJ | 학술논문

本文提出了一种能够分析多摄像机非重叠视域中运动目标行为之间时空相关性的方法。该方法基于特征空间中目标活动模式的相似性和活动空间的关联性，将摄像机网络中每个视域分为多个有意义的语意活动区域；利用交叉核典型相关分析（XKCCA ）分析语意活动区域之间的时空相关性，得到摄像机网络的拓扑关系，该拓扑关系能够反映目标在跨摄像机的语意区域之间运动的时空信息；将这些信息有效地融入到跨摄像机的目标再确认过程中，有利于排除虚假目标，提高跨摄像机目标再确认的准确度。与现有的方法相比，本文方法不依赖于个体目标的跟踪，实验结果表明本方法在复杂、拥挤、低帧频和低分辨率的多摄像机视频监控网络中能够有效地理解和分析视频内容，更准确的实现跨摄像机目标再确认。
본문제출료일충능구분석다섭상궤비중첩시역중운동목표행위지간시공상관성적방법。해방법기우특정공간중목표활동모식적상사성화활동공간적관련성，장섭상궤망락중매개시역분위다개유의의적어의활동구역；이용교차핵전형상관분석（XKCCA ）분석어의활동구역지간적시공상관성，득도섭상궤망락적탁복관계，해탁복관계능구반영목표재과섭상궤적어의구역지간운동적시공신식；장저사신식유효지융입도과섭상궤적목표재학인과정중，유리우배제허가목표，제고과섭상궤목표재학인적준학도。여현유적방법상비，본문방법불의뢰우개체목표적근종，실험결과표명본방법재복잡、옹제、저정빈화저분변솔적다섭상궤시빈감공망락중능구유효지리해화분석시빈내용，경준학적실현과섭상궤목표재학인。
This paper proposes an approach to analyze the temporal and spatial correlations between objective activities from multiple non-overlapping camera network .Based on the similarity of moving models and the relationship of moving space ,each vi-sion field of camera network is segmented into semantic active regions automatically .Then a Cross Kernel Canonical Correlation Analysis is implemented to explore the correlations between these active regions and the topology of the camera network .This topol-ogy can reflect the temporal and spatial information of objectives cross multi-cameras and improve the accuracy of objects re-identi-fication by removing false objects .Compared with existing methods ,our approach does not depend on the individual tracking and is efficient in complex and crowed scene .The experiment results show that our approach performs effectively and efficiently in multi camera surveillance network .