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Description: visibility graph code developed on matlab, which uses astar search algorithm and minkowski difference - developed and updated from the previosly uploaded java source code
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Size: 7168 |
Author: jackass243 |
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Description: 采用多假设检验法实现多目标跟踪，建立了多目标跟踪/视频监控平台，结合卡尔曼滤波预测目标轨迹。用户可以自己修改相关代码。-This code complete multiple object tracking/multiple target tracking/multi target tracking/multi object tracking using multiple hypothesis test/multi hypothesis test, builds up a visual surveillance (video surveillance) system, and explores kalman filter to predict tragectory of objects. Experimental results demonstrate its outperformance.
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Size: 46080 |
Author: 朱亮亮 |
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Description: 主成分分析.mht：介绍主成分分析的文章
edgepick.m：本程序的目的是实现边缘检测
drawprim.m：找到最大主分量所在的位置，从而在原图象中绘出
practical.m：一个主分量的程序，边缘检测和主分量提取
prin.m：该程序是用princomp函数来提取矩阵的主成分-Principal component analysis. Mht: the article describes the principal component analysis edgepick.m: The purpose of this program is to achieve edge detection drawprim.m: to find the location of the maximum principal component, which in the original image in the draw practical.m: a principal components process, edge detection and principal component extraction prin.m: princomp function of the program is to extract the principal component matrix
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Size: 17408 |
Author: 李仕诚 |
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Description: Implementation of the Murty algorithm to obtain the best K assignments. Includes the implementation of the Jonker-Volgenant algorithm.
Usual applications are multiple target tracking algorithms, Joint Probabilistic Data Association (JPDA), Multiple Hypothesis Tracking (MHT), Global Nearest Neighbours (GNN), etc.
Based on the original code by Jonker-Volgenant, and the Murty Matlab implementation by Eric Trautmann
Can be used both from Java or Matlab.
Time for a 100x100 assignment problem, with k=20:
• Matlab implementation: 54.5 sec
• Java implementation: 1 sec
-Implementation of the Murty algorithm to obtain the best K assignments. Includes the implementation of the Jonker-Volgenant algorithm.
Usual applications are multiple target tracking algorithms, Joint Probabilistic Data Association (JPDA), Multiple Hypothesis Tracking (MHT), Global Nearest Neighbours (GNN), etc.
Based on the original code by Jonker-Volgenant, and the Murty Matlab implementation by Eric Trautmann
Can be used both from Java or Matlab.
Time for a 100x100 assignment problem, with k=20:
• Matlab implementation: 54.5 sec
• Java implementation: 1 sec
Platform: |
Size: 27648 |
Author: hansen |
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