/multitarget-tracking

Multi target tracking using Sequential Monte Carlo approximation methods

Primary LanguageC++OtherNOASSERTION

Multitarget tracking

A multi target tracker based on Gaussian Mixture Probability Density Hypothesis Density Filter using Determinantal Point Processes pruning.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

  • CMake 2.8 or newer
  • OpenCV 3.4 (DNN library is required)
  • Eigen 3.2

Installating

Download the project:

git clone https://github.com/fjorquerauribe/multitarget-tracking.git

Build the project:

cd multitarget-tracking
mkdir build && cd build
cmake ..
make

Running the test

Download the MOT Challenge datasets https://motchallenge.net/

Create a symbolic link to the MOT Challenge datasets folder:

ln -s path/to/datasets/ data

Copy script to run Gaussian Mixture PHD filter:

cp ../scripts/start_gm_phd.sh .

Example: run Gaussian Mixture PHD filter over MOT16-02 sequence with public detections:

./start_gm_phd.sh MOT16 train MOT16-02 public 1

Example 2: run PHD filter and YOLO detector over MOT16-02 sequence (we assume YOLO .cfg, .weights and .names files are into data/yolo folder)

./start_phd.sh MOT16 train MOT16-02 100 yolo 0.5

Demo

Demo video https://www.youtube.com/watch?v=yVi9aQtO6fU

Authors

See also the list of contributors who participated in this project.

License

This project is licensed under the Apache 2 license - see the LICENSE.txt file for details.