Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Where is lambda in Equation 5 #112

Open
Code-Gratefully opened this issue Oct 31, 2018 · 9 comments
Open

Where is lambda in Equation 5 #112

Code-Gratefully opened this issue Oct 31, 2018 · 9 comments

Comments

@Code-Gratefully
Copy link

I'm trying to adjust the weights between the Karman filter results (location) and the features (appearance). Can anyone please kindly help?

@VellalaVineethKumar
Copy link

@ErnestCheung even I was searching for the same did you find?

@andreholz
Copy link

I would be interested in the same. Did they maybe set it to 0, and hence it is not included?

@nwojke
Copy link
Owner

nwojke commented Apr 30, 2019

Hi, sorry for the late reply. The question has come up a few times already. Unfortunately, our final implementation doesn't contain any lambda at all (as we set it to 0). Instead, we have a function that invalidates the appearance-based cost according to the Kalman filter gate here.

I hope this helps.

@RodMech
Copy link

RodMech commented Aug 20, 2019

@nwojke. Thanks for your comments, they are much appreciated. I have a couple of questions regarding the current implementation of the cost matrix:
Are there any remarkable reasons why you did not implemented the cost matrix computation as explained in Eq.5?
Is the logic behind the current implementation better?
Thank you!

@pratikbhave2
Copy link

Hi @nwojke , I read some issues about Lambda and your clarification that you have assumed lambda as 0 and implemented the gating metric.
But I have a doubt:
you calculate the cost matrix using cosine distance, then you pass that cost_matrix to gate_cost_matrix which thresholds it based on mahalanobis threshold and then it is thresholded using cosine_max_threshold. (I hope I have understood the code in the right way)

Why would you need to do Mahalanobis thresholding when the cost matrix calculation is purely based on cosine distance?

I hope my question is not too confusing!

@EricThomson
Copy link

@pratikbhave2 this way the kalman-based Mahalanobis metric is still being used as a kind of mask to filter out wildly improbable locations.

@michael-camilleri
Copy link

I implemented it in my fork of the repository (can be found here: https://github.com/michael-camilleri/deep_sort)

@kameel2311
Copy link

@michael-camilleri Thank you for your code, but I have been trying with changing Lambda from 0 to 1 and so effect on the ID was seen , any idea why that could be ? To implement your code I only replaced the Tracker.py by your own Tracker.py file

@michael-camilleri
Copy link

michael-camilleri commented May 18, 2021 via email

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

9 participants