RGBD-RF

This is a very basic header-only Random Forest library implementation.

To be able to use the library it is necessary to provide 4 things:

• Provide an implementation of a rf::SplitCandidate
• Something callable that generates an instance of a rf::SplitCandidate
• Wrap your data with a rf::TrainSet
• Provide the parameters for the training

examples

• UniversityOfWashingtonRGBDObjectDataset: Using a Random Forest for RGB-D images classification.