文件名称:find--k-best-1.00
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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
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
(系统自动生成,下载前可以参看下载内容)
下载文件列表
java-k-best-1.00/src/com/google/code/javakbest/Murty.java
java-k-best-1.00/src/com/google/code/javakbest/JVC.java
java-k-best-1.00/src/com/google/code/javakbest/PartitionNode.java
java-k-best-1.00/src/com/google/code/javakbest/Test.java
java-k-best-1.00/src/com/google/code/javakbest/Node.java
java-k-best-1.00/README.TXT
java-k-best-1.00/java-k-best.jar
java-k-best-1.00/findkbest.m
java-k-best-1.00/LICENSE
java-k-best-1.00/src/com/google/code/javakbest/
java-k-best-1.00/src/com/google/code/
java-k-best-1.00/src/com/google/
java-k-best-1.00/src/com/
java-k-best-1.00/src/
java-k-best-1.00/
java-k-best-1.00/src/com/google/code/javakbest/JVC.java
java-k-best-1.00/src/com/google/code/javakbest/PartitionNode.java
java-k-best-1.00/src/com/google/code/javakbest/Test.java
java-k-best-1.00/src/com/google/code/javakbest/Node.java
java-k-best-1.00/README.TXT
java-k-best-1.00/java-k-best.jar
java-k-best-1.00/findkbest.m
java-k-best-1.00/LICENSE
java-k-best-1.00/src/com/google/code/javakbest/
java-k-best-1.00/src/com/google/code/
java-k-best-1.00/src/com/google/
java-k-best-1.00/src/com/
java-k-best-1.00/src/
java-k-best-1.00/
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