CAJ | 학술논문

提出一种改进的适用于智能安防领域中离岗检测的目标跟踪算法，该算法结合均值漂移算法和粒子滤波算法的优点，先使用均值漂移算法对目标进行预跟踪，然后在此基础上使用粒子滤波对目标精确定位，在保证了跟踪准确率的前提下缩短了算法的计算时间。此外，针对监控视频大多分辨率低，目标辨识度不高等特点，在本文中，原始视频流的灰度信息和纹理信息被作为待跟踪目标的特征。实验结果证明，采用该混合特征的目标跟踪算法比其他同类算法在目标跟踪的准确率和实时性上具有更好的表现，能够适应更广泛的视频场景。
제출일충개진적괄용우지능안방영역중리강검측적목표근종산법，해산법결합균치표이산법화입자려파산법적우점，선사용균치표이산법대목표진행예근종，연후재차기출상사용입자려파대목표정학정위，재보증료근종준학솔적전제하축단료산법적계산시간。차외，침대감공시빈대다분변솔저，목표변식도불고등특점，재본문중，원시시빈류적회도신식화문리신식피작위대근종목표적특정。실험결과증명，채용해혼합특정적목표근종산법비기타동류산법재목표근종적준학솔화실시성상구유경호적표현，능구괄응경엄범적시빈장경。
In this paper,we propose an improved obj ect tracing algorithm which is suitable for off-position detection in intelligent security filed.This algorithm takes advantage of mean shift and particle filter,pre-traces the obj ect by the mean-shift algorithm and then calculates the accurate position by particle algorithm,which shortens computing time on the premise of insuring tracing accuracy.Besides,according to the problem that the low-resolution and low contrast of surveillance vide-o,a new hybrid feature based on the gray scale information and texture information is regarded as the main feature of obj ect in video scene.At last,experiment results prove that the improved obj ect tracing algorithm with hybrid feature have better performance of tracking accuracy and real-time,which is applied more widely than other algorithms.