Assume that I have a camera pointing in a specific direction. I know the Euclidean distance (Real world distance) of the camera to a fixed point, X (mm). Using YOLOv3 I have detected all the occurences of an object and have the bounding boxes and their centers. I also am able to determine the Euclidean distance of the camera to all bounding box centers. I have the availability to the following measures:
focal length,
image height (px), ## Photo
image width (px), ## Photo
Real object height (mm),
Real object width (mm),
sensor height (mm),
sensor width (mm),
pixel size ($mu$m),
Field of view (vertical),
Field of view (horizontal)
and the following calculated measures:
0. The pixel-coordinates of every single bounding box center.
1. Euclidean distance from camera to all instances of a specific and detected object
2. object height and width (in pixels) # used to calculate 1.
3. Angle made by between every pair of bounding box centers relative a fixed point on the image (actually, an epipole determined by the use of a second image)
Now, what I would like to do is to calculate the Euclidean distance (Real world distance) between the objects in the photo. I naively thought that knowing the pixel distance and the pixel size woul be enough but apparently I was mistaken.
Any insight would be greatly appreciated.
Thanks!
