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.