Class 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: <> As long as original authors implementation: <> Implementation of training algorithm is placed in separately here due to 3d-party dependencies: <> GOTURN architecture goturn.prototxt and trained model goturn.caffemodel are accessible on opencv_extra GitHub repository.
    • Constructor Detail

      • TrackerGOTURN

        protected TrackerGOTURN​(long addr)
    • Method Detail

      • __fromPtr__

        public static TrackerGOTURN __fromPtr__​(long addr)
      • create

        public static TrackerGOTURN create()
        automatically generated
      • finalize

        protected void finalize()
                         throws java.lang.Throwable
        finalize in class Tracker