Some basic questions about the paper about goturn

[serkansulun]

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

[davheld]

1-2) That is correct

3. 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).

[serkansulun]

Thanks for the quick answer.

3. 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

[davheld]

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.

[serkansulun]

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

[davheld]

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.

See Table 1 http://davheld.github.io/GOTURN/GOTURN.pdf For the other questions - I'm not sure, sorry. You'd have to check with VOT or look at their code Best of luck!.

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