Motion detection and object tracking lecture

Meeting Recording:

https://us02web.zoom.us/rec/share/uxYH8RxkGWaWO6BZB9xhYUX4i0NwA_9I1vVAnzQu13FPZ8a-WzdGWnrhjtUCvYkV.V8y4zVOLEwXnF7zL

Access Passcode: u^k1dim2

Agenda

• Problem statement
• Basic approach
  • Optical flow
  • Lukas-Kanade algorithm
• Tracking-by-detection
  • Kalman filter
  • Hungarian algorithm
  • SORT
  • DeepSORT
• Tracking with network flows

Links used

1. Article about Optical Flow: https://nanonets.com/blog/optical-flow/
2. OpenCV tutorial on Optical Flow: https://docs.opencv.org/master/d4/dee/tutorial_optical_flow.html
3. The least squares fitting explanation: https://mathworld.wolfram.com/LeastSquaresFitting.html
4. Paper "Pyramidal Implementation of the Lucas Kanade Feature Tracker": http://robots.stanford.edu/cs223b04/algo_tracking.pdf
5. Kalman filer site: https://www.kalmanfilter.net/alphabeta.html
6. Explanation of Hungarian algorithm: https://brilliant.org/wiki/hungarian-matching/#the-hungarian-algorithm-using-an-adjacency-matrix
7. Original SORT paper: https://arxiv.org/abs/1602.00763
8. Original DeepSORT paper: https://arxiv.org/abs/1703.07402
9. Fascinating TUM lecture about MOT: https://www.youtube.com/watch?v=BR3Y5bAz5Dw&t
10. Super useful practical article from experienced engineer, but hard to read without a prior knowledge: https://habr.com/ru/company/recognitor/blog/505694/

Task

Subtask	Points
Add people tracker to the video, submit your code + video result (in my Telegram). Play with init/lifespan constants to obtain better results.	10
Compare trackers without appearance metrics (SORT / Norfair etc.) to ones that use it (DeepSORT / FairMOT etc.)	10
Online presentation of your code (Google Meet/Zoom): show me, how you obtained your video results	10
Answer my additional questions	5

Deadline

Must be submitted not later than 05.05.2021.

Description of given code

In this repo you can also find instructions along with the blank.py script that:

• reads video frame-by-frame in a format used by YOLOv5,
• performs object detection (particularly, detects people),
• writes video with detected bounding boxes on the video.

Installation

Highly recommend to use virtual environment instead of global interpretator.

In your terminal:

1. git clone https://github.com/ultralytics/yolov5.git
2. cd yolov5
3. pip install -r requirements.txt
4. cd ..

Weights

You can download weights for YOLOv5 from its official GitHub repo.

Usage

In your terminal:

python blank.py --input-path $INPUT_VIDEO --save-path $OUTPUT_VIDEO --weights-path $PATH_TO_MODEL_WEIGHTS