Topic: Object/target tracking is a crucial component of many computer vision systems. Their aim is to track object image on the image plane from one video frame to the next one. Video tracking methods using correlation filters (e.g., KCF tracker) are frequently used as they are capable of achieving real time performance for long-term tracking on a embedded computing platforms, e.g., on-drone.
Exercise: Create a Python script file and perform the following tasks:
- Import OpenCV library.
- Open a video stream.
- Select KCF as the desired tracker from OpenCV library.
- Track the desired object in the video stream using KCF tracker.
You can download the exercise’s resources from here.
Material for better understanding: A lecture on visual object tracking, e.g., from: https://icarus.csd.auth.gr/2d-visual-object-tracking-lecture/
Knowledge Assessment questionnaire: https://aiia.csd.auth.gr/gr/cvml-knowledge-self-assessment/
For the solutions to the exercises, please contact koroniioanna@csd.auth.gr