检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:林洋 樊春运 LIN Yang;FAN Chunyun(Jilin Innovation Center of Distance Education Technologies,Changchun 130022,China;Office of Informatization Management and Planning,Northeast Normal University,Changchun 130022,China)
机构地区:[1]吉林省远程教育技术科技创新中心,长春130022 [2]东北师范大学信息化管理与规划办公室,长春130022
出 处:《计算机工程》2019年第12期267-273,共7页Computer Engineering
基 金:吉林省科技发展计划项目(20190902010TC);吉林省职业教育与成人教育教学改革研究课题(2018ZCY188)
摘 要:基于视频图像特征点配准的目标跟踪算法无法兼顾精确性、实时性和鲁棒性,针对该问题,提出一种基于特征位置预测与邻域一致性约束的视频特征快速配准算法。以标注点与目标标记框为模板,通过ORB特征匹配与邻域一致性检验,获得帧间标注点集的对应关系,并计算点集间的尺度变换以确定当前目标框,利用多帧已知标注点位置信息与运动连续性进行多项式回归预测,得到标注点集的位置。在此基础上,对特征点进行局部搜索、提取和描述,根据邻域一致性约束,利用邻域内的支持特征点集实现标注点的稳健匹配。实验结果表明,该算法可对多姿态目标特征点进行配准,与GMS、ORB、SIFT和SURF算法相比,该算法的实时性、准确性和鲁棒性明显提高。Existing target tracking algorithms based on video features points registration cannot balance precision,real-time performance and robustness.To address the problem,this paper proposes a fast video feature registration algorithm based on feature location prediction and constraints of neighborhood consistency.The algorithm takes labeled points and target label box as templates,and uses ORB feature matching and neighborhood consistency checking to obtain relations between inter-frame labeled point sets.The scale transform between point sets are also calculated to determine the current target box.The location of labeled point sets is obtained using polynomial regression prediction based on the location of known labeled points of multiple frames and motion continuity.On this basis,local search,extraction and description are performed on feature points,and robust matching of labeled points is implemented using assistant feature point sets in neighborhood according to neighborhood consistency constraints.Experimental results show that the proposed algorithm can implement registration of feature points of a multi-pose target,and has an obviously improved real-time performance,accuracy and robustness compared with GMS,ORB,SIFT and SURF algorithms.
关 键 词:位置预测 多项式回归 运动连续性 邻域一致性 视频特征跟踪
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.40