You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Currently when you have multiple regions defined and they are stacked next to each other, there is still a high chance of both regions registering an object, as the object detection is able to recognize 1/4 of a body as a human with fairly high accuracy. This means that you will be registering multiple people where only 1 exists fairly regularly.
I think the best solution to this problem is to encourage overlapping regions but to have an underlying motion detection engine watching the entire stream instead of only the defined regions. If it was watching the whole scene, it could then choose the region in which the moving object was located and turn off the other regions which he was only partially located, and so remove duplicates. If each region overlapped each other region by 50%, it would be close to impossible for any object to be detected twice because there would be ample space around it for it to exist entirely within a single region, and other regions that it's only partially in could be excluded from detection.
Not only would this remove duplicates, but it would also increase accuracy because the object you wanted would pretty much always be fully or very close to fully contained within a region, and regions could be sized correctly so that the object could fill most of the frame of the region.
This would also reduce CPU usage as most of the time, a single moving object could be processed entirely within a single region rather than spanning multiple regions.
This is a bit difficult of a concept to put into words, so let me know if you'd like me to explain further, I could draw what it looks like.
The text was updated successfully, but these errors were encountered:
Currently when you have multiple regions defined and they are stacked next to each other, there is still a high chance of both regions registering an object, as the object detection is able to recognize 1/4 of a body as a human with fairly high accuracy. This means that you will be registering multiple people where only 1 exists fairly regularly.
I think the best solution to this problem is to encourage overlapping regions but to have an underlying motion detection engine watching the entire stream instead of only the defined regions. If it was watching the whole scene, it could then choose the region in which the moving object was located and turn off the other regions which he was only partially located, and so remove duplicates. If each region overlapped each other region by 50%, it would be close to impossible for any object to be detected twice because there would be ample space around it for it to exist entirely within a single region, and other regions that it's only partially in could be excluded from detection.
Not only would this remove duplicates, but it would also increase accuracy because the object you wanted would pretty much always be fully or very close to fully contained within a region, and regions could be sized correctly so that the object could fill most of the frame of the region.
This would also reduce CPU usage as most of the time, a single moving object could be processed entirely within a single region rather than spanning multiple regions.
This is a bit difficult of a concept to put into words, so let me know if you'd like me to explain further, I could draw what it looks like.
The text was updated successfully, but these errors were encountered: