Tracking of Moving Objects by the Visual Servoing System

        This project makes use of a computer vision system for object localization and tracking, which consists of a camera, a Raspberry Pi control unit and a servomotor. Video record captured by the camera is processed and in the real-time reproduced on the computer screen. Computer is connected with the control unit used for driving the servomotor which starts the camera and directs it in the real-time to the specified object. The algorithms for object localization and tracking are implemented in the programming language Python, along with the open-source library OpenCV. The resulting evaluation of the algorithms is based on the set of various moving objects.

Project workflow

Step 1.  Designing the visual servoing system

        

Step 2.  Implementing the color tracking algorithm

Step 3.  Implementing the backprojection algorithm

Step 4.  Implementing the absolute difference algorithm

Step 5.  Implementing the optical flow algorithm

Step 6.  Analyzing the results for different algorithms

Run the project on Windows

Step 1.  Clone the repository:

cd %HOMEPATH%

git clone https://github.com/Doc1996/moving-object-tracking

Step 2.  Create the virtual environment and install dependencies:

cd %HOMEPATH%\moving-object-tracking

python -m pip install --upgrade pip
python -m pip install --user virtualenv

python -m venv python-virtual-environment
.\python-virtual-environment\Scripts\activate

.\WINDOWS_INSTALLING_PACKAGES.bat

Step 3.  Modify the changeable variables in MOT_constants.py

Step 4.  Run the program:

cd %HOMEPATH%\moving-object-tracking

.\python-virtual-environment\Scripts\activate

.\WINDOWS_OBJECT_LOCALIZATION_APPLICATION.bat

Run the project on Linux

Step 1.  Clone the repository:

cd $HOME

git clone https://github.com/Doc1996/moving-object-tracking

Step 2.  Create the virtual environment and install dependencies:

cd $HOME/moving-object-tracking

python3 -m pip install --upgrade pip
python3 -m pip install --user virtualenv

python3 -m venv python-virtual-environment
source python-virtual-environment/bin/activate

source LINUX_INSTALLING_PACKAGES.sh

Step 3.  Modify the changeable variables in MOT_constants.py

Step 4.  Run the program:

cd $HOME/moving-object-tracking

source python-virtual-environment/bin/activate

source LINUX_OBJECT_LOCALIZATION_APPLICATION.sh