/ObjectTracking

Mini Project-II: Tracking the objects in consecutive video frames and represent them by an assigned id number using centroid tracking strategy

Primary LanguagePython

Object Tracking

Object tracking is the process of:

  1. Taking an initial set of object detections
  2. Creating a unique ID for each of the initial detections
  3. And then tracking each of the objects as they move around frames in a video, maintaining the assignment of unique IDs

As descibed in first step, we should detect the objects in each frame of video. Here YOLO object detection is used to detect the object in image/video-frames. Implemention of yolo is in ObjectTracker.py. Next two steps are implemented in CentroidTracking/centroidtracker.py.

To run on video file:
python ObjectTracker.py --input videos/car_chase_01.mp4 --confidence 0.5 --threshold 0.3
To run on web-camera:
python ObjectTracker.py --input camera --confidence 0.5 --threshold 0.3

references/credit:

  1. YOLO object detection with OpenCV
  2. Simple object tracking with OpenCV