Often occlusions don’t matter in practice for dense object tracking e.g. counting people entering a bus or measuring gym equipment utilization you actually don’t care if the person IDs switch.
Centroid tracking works well in practice at 2 FPS for the bus use case and several others.
More complex approaches have their place but an important limiting factor (e.g. in the bus project I worked on) is that often the hardware required to run a more complex approach at a higher frame rate is too expensive to be feasible.
There are definitely limitations to centroid tracking and use cases where it doesn’t work like if you need to track specific faces moving through a crowd but it’s a useful tool that has its place in practice.
Your blog post is awesome, I’m just pointing out that a simpler method often works well in practice and is much less intimidating for beginners :)
Centroid tracking works well in practice at 2 FPS for the bus use case and several others.
More complex approaches have their place but an important limiting factor (e.g. in the bus project I worked on) is that often the hardware required to run a more complex approach at a higher frame rate is too expensive to be feasible.
There are definitely limitations to centroid tracking and use cases where it doesn’t work like if you need to track specific faces moving through a crowd but it’s a useful tool that has its place in practice.
Your blog post is awesome, I’m just pointing out that a simpler method often works well in practice and is much less intimidating for beginners :)