Comments (1)
adipandas
commented on May 14, 2024
1
Hi @sinamsl,
The method used for tracking in the current implementation would not ensure assigning the same ID if the lost object is detected after the max_lost steps. Additionally, using a high value of max_lost would make the deletion of the tracked objects problematic when they are out of the camera frame.
To ensure the same id is being assigned once the object is re-detected, I recommend you to look into techniques for tracking with re-identification.
I am interested in including a version of object re-identification in this repository. But I haven't been able to make time for this.
I would suggest you refer to approaches similar to this implementation for more details.
Best regards,
Aditya.
from multi-object-tracker.
Related Issues (20)
- How did you choose the Process & Measurement noise? HOT 1
- In the SORT tracker, IOU threshold is not working. HOT 2
- what is max_lost? HOT 1
- Do you have any plan to add V-IOU Tracker? HOT 1
- AttributeError: 'SORT' object has no attribute 'track' HOT 1
- Is there any tracker prediction? HOT 2
- Using Hyperparameter tuning library (Guild.ai or Ray tune) HOT 1
- x,y,z values alvays gives -1,-1,-1 HOT 1
- Getting the exact same result when changing tracker type HOT 1
- Bug in detector_YOLOv3.py
- Adding Deepsort Tracker HOT 1
- Project dependencies may have API risk issues HOT 1
- Starting example is not runnable (uses track method instead of update) HOT 1
- PyPI Package HOT 8
- Plz add Requirements HOT 1
- class_ids is not considered in the tracking HOT 1
- To predict a detection without a detection by a detector HOT 1
- Bug: SORT always same iou_threshold HOT 1
- Fix cv2 version checking in motrackers.detectors.yolo.py HOT 2
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from multi-object-tracker.