KCF-DSST-py

Python implementation of DSST tracking algorithm based on KCF tracker.

In [Baseline 3], the DSST scale estimation algorithm is added to the original KCF Tracker. Based on the python implementation of KCF Tracker, see [Baseline 2], the code of DSST is translated from C++ and added to the KCF in python.

Requirements

• Python 2.7 (or 3)
• NumPy
• Numba (needed if you want to use the hog feature)
• OpenCV (ensure that you can import cv2 in python)

Baseline

Some implementations of KCF and DSST algorithms.

1. KCF Tracker in C++

C++ KCF Tracker: Original C++ implementation of Kernelized Correlation Filter (KCF) [1, 2].

2. KCF Tracker in Python

KCF tracker in Python: Python implementation of KCF Tracker.

3. DSST Tracker in C++

KCF-DSST: C++ implementation of Discriminative Scale Space Tracker (DSST) [3].

Reference

[1] J. F. Henriques, R. Caseiro, P. Martins, J. Batista, "High-Speed Tracking with Kernelized Correlation Filters", TPAMI 2015.

[2] J. F. Henriques, R. Caseiro, P. Martins, J. Batista, "Exploiting the Circulant Structure of Tracking-by-detection with Kernels", ECCV 2012.

[3] M. Danelljan, G. Häger, F. Shahbaz Khan, and M. Felsberg. "Accurate scale estimation for robust visual tracking". In Proceedings of the British Machine Vision Conference (BMVC), 2014.