What is this?

Nodelet to train jsk_perception/SlidingWindowObjectDetector using binary support vector machine. The object is assigned a label of +1 and -1 otherwise. The SVM used is from the OpenCV Library with default set to RBF Kernel and 10-Fold Cross Validations.

Note that this nodelet produces two output files of ”.xml” format to the working directory.

  • 1) Trained Classifier - this file the trained object SVM. Dont edit this file.
  • 2) sliding_window_trainer_manifest.xml - this file contains parameters of the trainer that are not in (1). Information such as trainer window size, save directory, etc.


  • ~dataset_path (string, default: training_dataset)

    Folder name where the training sets resides.

  • ~object_dataset_filename (string)

    Rosbag file name of the object (positive) training set

  • ~nonobject_dataset_filename (string)

    Rosbag file name of the non-object (negative) training set

  • ~classifier_name (string)

    Name of the trained svm output file

  • ~swindow_x (int, default: 32)

    Window width

  • ~swindow_y (int, default: 64)

    Window height