Description
java-k-best is a free and open-source implementation of the Murty algorithm to obtain the best K assignments. The project includes the implementation of the Jonker-Volgenant algorithm.
The usual applications are multiple target tracking algorithms, Joint Probabilistic Data Association (JPDA), Multiple Hypothesis Tracking (MHT), Global Nearest Neighbours (GNN), etc.
Moreover, you will be able to use java-k-best both from Java or Matlab.
This is time for a 100x100 assignment problem, with k=20:
· Matlab implementation: 54.5 sec
· Java implementation: 1 sec
java-k-best is a cross-platform utility capable of running on any operating system that comes with Java support (e.g. Mac OS X, Windows, Linux).
User Reviews for java-k-best FOR MAC 1
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for java-k-best FOR MAC
java-k-best for Mac offers an efficient and quick solution using the Murty algorithm. A great tool for multiple target tracking and more.