Hi there,
I’m testing out the YOLOv8 detector using the code here:
I’m currently testing detecting people standing approx. 1,600 mm from the front of the camera (ZED X).
My question is regarding the spatial information in the detection ObjectData
. The model is able to detect person
classes well, however, I get very different dimensions
and locations
data depending on whether the person has their arms stretched out to the side, or their arms by their sides.
Arms by side
"position_x": 0.08632095903158188,
"position_y": -0.1568923145532608,
"position_z": 1.589307188987732,
"dimensions_width": 0.6560447812080383,
"dimensions_height": 1.9906524419784546,
"dimensions_length": 0.656044602394104,
The units are in meters. Based on the location of the person from the camera, and the sl.COORDINATE_SYSTEM.IMAGE
, these numbers are reasonable.
Arms stretched out to the side
"position_x": 0.3633350431919098,
"position_y": -0.35973766446113586,
"position_z": 3.2438979148864746,
"dimensions_width": 3.4917516708374023,
"dimensions_height": 4.045949935913086,
"dimensions_length": 3.4917516708374023,
I’d expect the dimensions_width
value to increase as the person’s arms are stretched out horizontally, however, I didn’t expect the dimensions_height
value to change; it’s doubled.
I also didn’t expect the position_z
value to change given the person is standing at the same distance from the camera in both scenarios, however, it’s doubled as well.
What could cause these values to change so much based on the position of the person’s arms?
Appreciate any insights, thanks!