This class is used to track multiple objects using the specified tracker algorithm.
Base abstract class for the long-term tracker:
the Boosting tracker
This is a real-time object tracking based on a novel on-line version of the AdaBoost algorithm.
the CSRT tracker
The implementation is based on CITE: Lukezic_IJCV2018 Discriminative Correlation Filter with Channel and Spatial Reliability
the GOTURN (Generic Object Tracking Using Regression Networks) tracker
GOTURN (CITE: GOTURN) is kind of trackers based on Convolutional Neural Networks (CNN).
the KCF (Kernelized Correlation Filter) tracker
KCF is a novel tracking framework that utilizes properties of circulant matrix to enhance the processing speed.
the Median Flow tracker
Implementation of a paper CITE: MedianFlow .
The MIL algorithm trains a classifier in an online manner to separate the object from the
the MOSSE (Minimum Output Sum of Squared %Error) tracker
The implementation is based on CITE: MOSSE Visual Object Tracking using Adaptive Correlation Filters
Note: this tracker works with grayscale images, if passed bgr ones, they will get converted internally.
the TLD (Tracking, learning and detection) tracker
TLD is a novel tracking framework that explicitly decomposes the long-term tracking task into
tracking, learning and detection.