Comments (6)
I might have discovered some things, looking at the code, please tell me if I'm wrong somewhere.
1- We are only using annotated frames, eg. only frame 6 and 11. Frame 6 becomes previous, frame 11 becomes current.
2- In augmentation we shift and scale the ground-truth box in the current frame, and crop twice the area around the shifted box, only to define a new synthetic search region. While getting labels (coordinates relative to the new search region), we still use the not-shifted ground-truth box coordinates.
Are these correct?
I'm still not clear about question 3.
Thanks
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1-2) That is correct
- After figuring out what part of the image we want to crop, we crop that region, and then we resize the cropped region to the fixed-size input for the network (227 x 227).
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Thanks for the quick answer.
- Do we do it by matching the shorter side to 227 and zero padding the remaining area? Do the ground-truth bounding box coordinates stay the same?
Thanks
from goturn.
We do it by resizing both sides to 227x227. You can try the padding approach if you wish. The ground-truth bounding box coordinates are resized accordingly.
from goturn.
Hi again David,
To test my implementation, I want to use accuracy and robustness errors, instead of ranking. In your paper I couldn't find a direct reference to these metrics but I have some idea, so please let me know if I'm wrong somewhere.
1- Accuracy is simply intersection-over-union value, between ground-truth and predicted boxes.
2- When the accuracy becomes zero (no intersection), the tracker is reinitialized, meaning the ground-truth box is provided for the next frame. Or is it reinitialized n frames later?
3- Robustness error is number of reinitializations divided by number of frames.
4- Are these two measures averaged first over frames (in a single sequence) then over all sequences; or over all frames in all sequences at once?
Thanks in advance
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Related Issues (20)
- Make error HOT 1
- Attempting to use an MPI routine before initializing MPI HOT 1
- Segmentation fault HOT 3
- stuck with basic issue HOT 1
- The Annotation cannot be loaded
- Understanding the ground truth HOT 1
- integrate GOTURN in the VOT toolkit
- How to deal with error accumulation?
- train without init model?
- Train on Images Only HOT 1
- How to combine GOTURN with another online algorithm?
- Why didn't my loss drop in training?
- 26048 Segmentation fault (core dumped) HOT 1
- Run tracker on single video file
- ‘caffe::Net’ is not a template HOT 3
- undefined reference
- location of annotation in alov300++ dataset is incorrect
- What is the performance for tiny moving objects?
- Segmentation fault on running the tracker test
- The link to pretrained tracker model is invalid. HOT 2
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