搜索结果: 1-5 共查到“信息处理技术 MEAN-SHIFT”相关记录5条 . 查询时间(0.07 秒)
URBAN DENSITY INDICES USING MEAN SHIFT-BASED UPSAMPLED ELEVATION DATA
urban density LiDA Neural Networks
2015/5/7
Urban density is an important factor for several fields, e.g. urban design, planning and land management. Modern remote sensors deliver ample information for the estimation of specific urban land cl...
基于特征贡献度的Mean Shift目标跟踪
Mean Shift 特征贡献度 模板匹配 核直方图 特征提取
2016/5/4
为有效提高Mean Shift 算法的模板匹配精确度，采用基于特征贡献度的Mean Shift目标跟踪方法，对不同贡献度的特征向量赋予不同的权重，以彰显目标特征、抑制背景因素。分别介绍传统Mean Shift目标跟踪算法和基于特征贡献度的Mean Shift算法，并针对多组视频进行实验验证与分析。结果表明，改进后的Mean Shift算法不仅能提高跟踪精度、提升系统的鲁棒性，而且对640 pixe...
由于在成像制导过程中需要实时处理大量的信息,为了在尽可能保留有效信息情况下降低计算量,采用了一种人眼视觉非均匀采样模型——对数极坐标模型,来压缩信息量以提高计算速度；另外,由于对数极坐标变换对目标形状具有旋转和缩放不变性,在跟踪非刚性变形目标时该模型能表现出很好的稳健性；考虑到在成像跟踪末段,质心、角点之类的跟踪方法会产生匹配点漂移,为了抑制匹配点漂移,采用基于目标强度特征的Mean Shift跟...
MEAN-SHIFT BLOB TRACKING WITH ADAPTIVE FEATURE SELECTION AND SCALE ADAPTATION
MEAN-SHIFT BLOB TRACKING FEATURE SELECTION SCALE ADAPTATION
2010/12/17
When the appearances of the tracked object and surrounding background change during tracking, fixed feature space tends to cause tracking failure. To address this problem, we propose a method to embed...
MEAN-SHIFT BLOB TRACKING WITH ADAPTIVE FEATURE SELECTION AND SCALE ADAPTATION
MEAN-SHIFT ADAPTIVE FEATURE SELECTION SCALE ADAPTATION
2010/12/17
When the appearances of the tracked object and surrounding background change during tracking, fixed feature space tends to cause tracking failure. To address this problem, we
propose a method to embe...