blefaudeux / gmphd

A Gaussian-Mixtures Probability Hypothesis Density (GM-PHD) filter for multitarget tracking in a bayesian framework
35 stars 14 forks source link

GM-PHD in Motion detector #2

Open Nuzhny007 opened 7 years ago

Nuzhny007 commented 7 years ago

Hi! It's not an issue - just a question. I'm interesting in area of motion detectors. You can see the project Multitarget-tracker: https://github.com/Smorodov/Multitarget-tracker I'm one of contributors. And it will be interesting to use your project for the comparing quality and performance of the different algorithms of the detection and tracking. May be you can give me some recommends for the integration GM-PHD to the our project? We have some regions (contours) after Background subtraction. And after...? In this file I added function GMPHDTracker with GMPHD (default parameters from your test): https://github.com/Nuzhny007/Multitarget-tracker/blob/gmphd/main.cpp GM-PHD is the replacement of the Hungrian+Kalman? If you can give me some advices it will be cool. Thank you!

blefaudeux commented 7 years ago

Hi Sergey, sorry for the delay, super busy right now. GMPHD and Hungrian+Kalman do not serve the same purpose if I'm not mistaken, since GMPHD does not handle the association problem. They're complimentary though, because GMPHD handles probabilistic noise (which is not the case for Hungrian, if I'm not mistaken again). In terms of questions that the algorithms answer, I would describe them (+KF), as:

In a nutshell (I don't have too much time unfortunately), it looks like GMPHD could be useful indeed, as a first step in your pipeline to try to clean up false detections, and the rest of the pipeline can stay the same

blefaudeux commented 7 years ago

p.s. the video is pretty neat !

Nuzhny007 commented 7 years ago

Hi! Thanks for the full answer! I try to use your GMPHD implementation after blobs detection algorithm. After I will write you about results.