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Evaluation of Clustering Methods for Finding Dominant Optical Flow Fields in Crowded Scenes

机译：在拥挤场景中寻找主导光流场的聚类方法的评估

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Günther Eibl; Norbert Brändle;
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年度 2012
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1. Histogram of Maximal Optical Flow Projection for Abnormal Events Detection in Crowded Scenes [J] . AngLi, ZhenjiangMiao, YigangCen, International Journal of Distributed Sensor Networks . 2015,第2期

机译：最大光学流量投影的直方图，用于在拥挤的场景中检测异常事件
2. A high accuracy flow segmentation method in crowded scenes based on streakline [J] . Xiaofei Wang, Xiaomin Yang, Xiaohai He, Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic . 2014,第3期

机译：基于条痕线的拥挤场景中高精度流分割方法
3. Identifying motion pathways in highly crowded scenes: A non-parametric tracklet clustering approach [J] . Allam S. Hassanein, Mohamed E. Hussein, Walid Gomaa, Computer vision and image understanding . 2020,第Feba期

机译：在高度拥挤的场景中识别运动路径：非参数小波聚类方法
4. Evaluation of Clustering Methods for Finding Dominant Optical Flow Fields in Crowded Scenes [C] . Gunther Eibl, Norbert Brandle International Conference on Pattern Recognition . 2008

机译：评估在拥挤场景中查找主导光学流场的聚类方法
5. The development and applications of a numerical method for compressible vorticity confinement in vortex-dominant flows. [D] . Hu, Guangchu. 2001

机译：涡旋主导流中可压缩涡度限制数值方法的发展与应用。
6. Dynamic 3D Scene Depth Reconstruction via Optical Flow Field Rectification [O] . You Yang, Qiong Liu, Rongrong Ji, -1

机译：通过光流场整流动态3D景深重建
7. Automatically determining dominant motions in crowded scenes by clustering partial feature trajectories [O] . Anil M. Cheriyadat, Richard J. Radke 2007

机译：通过聚类局部特征轨迹自动确定拥挤场景中的主导运动
8. Parametric Statistical Methods and Sample-Size Considerations for Dominant Lethal Experiments: The Use of Clustering to Achieve Approximate Normality [R] . Whorton, E. B. 1981

机译：主导致死实验的参数统计方法和样本大小考虑因素：使用聚类来实现近似正态性

Evaluation of Clustering Methods for Finding Dominant Optical Flow Fields in Crowded Scenes

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