From 2D images we can extract a limited range of information like width, height and color. These can be useful to determine the regions of interest in our images: street signs, lanes, or even roads.
However, for a more accurate detection, the depth perception
is crucial. Here comes the 3D reconstruction into play. Extracting a 3rd dimension, the depth, we can determine how far from the
camera the regions of interest are and consequently, their shape. This way we can distinguish the road from the obstacles (cars, pedestrians, curbstones) simply because we know that the road has an increasing distance from the camera while the objects have a constant distance (fig. 1).