KCF tracker in Python3

The project is based on the project, a Python2 version implementation of

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

The version of Python2 is translated from KCFcpp (Authors: Joao Faro, Christian Bailer, Joao F. Henriques), a C++ implementation of Kernelized Correlation Filters. Find more references and code of KCF at http://www.robots.ox.ac.uk/~joao/circulant/

Requirements

• Python3 (3.8 or later)
• NumPy
• Numba (needed if you want to use the hog feature)
• OpenCV

Here is an easy way to install, just execute the command under the project folder.

pip3 install -r requirements.txt

Use

Download the sources and execute

git clone git@github.com:discipleofhamilton/KCF-python.git # ssh
git clone https://github.com/discipleofhamilton/KCF-python.git # https
cd KCFpy
python run.py

It will open the default camera of your computer, you can also open a different camera or a video

python run.py 2

python run.py ./test.avi  

Limitation

KCF has 2 limitations:

1. Programming language problem: the execute speed of python is slower than C++.
2. Short-term tracking: KCF doesn't have fail-over strategy, it hard to re-track the object which it just lost.