Class TrackerGOTURN

java.lang.Object
org.opencv.video.Tracker
org.opencv.video.TrackerGOTURN

public class TrackerGOTURN extends Tracker
the GOTURN (Generic Object Tracking Using Regression Networks) tracker GOTURN (CITE: GOTURN) is kind of trackers based on Convolutional Neural Networks (CNN). While taking all advantages of CNN trackers, GOTURN is much faster due to offline training without online fine-tuning nature. GOTURN tracker addresses the problem of single target tracking: given a bounding box label of an object in the first frame of the video, we track that object through the rest of the video. NOTE: Current method of GOTURN does not handle occlusions; however, it is fairly robust to viewpoint changes, lighting changes, and deformations. Inputs of GOTURN are two RGB patches representing Target and Search patches resized to 227x227. Outputs of GOTURN are predicted bounding box coordinates, relative to Search patch coordinate system, in format X1,Y1,X2,Y2. Original paper is here: <http://davheld.github.io/GOTURN/GOTURN.pdf> As long as original authors implementation: <https://github.com/davheld/GOTURN#train-the-tracker> Implementation of training algorithm is placed in separately here due to 3d-party dependencies: <https://github.com/Auron-X/GOTURN_Training_Toolkit> GOTURN architecture goturn.prototxt and trained model goturn.caffemodel are accessible on opencv_extra GitHub repository.
  • Method Details

    • __fromPtr__

      public static TrackerGOTURN __fromPtr__(long addr)
    • create

      public static TrackerGOTURN create(TrackerGOTURN_Params parameters)
      Constructor
      Parameters:
      parameters - GOTURN parameters TrackerGOTURN::Params
      Returns:
      automatically generated
    • create

      public static TrackerGOTURN create()
      Constructor
      Returns:
      automatically generated
    • create

      public static TrackerGOTURN create(Net model)
      Constructor
      Parameters:
      model - pre-loaded GOTURN model
      Returns:
      automatically generated