When we capture images, we project the 3D world around us on a 2D image plane. So technically, we only have 2D information when we capture those photos. Since all the objects in that scene are projected onto a flat 2D plane, the depth information is lost. We have no way of knowing how far an object is from the camera or how the objects are positioned with respect to each other in the 3D space. This is where stereo vision comes into the picture.
Humans are very good at inferring depth information from the real world. The reason is that we have two eyes positioned a couple of inches from each other. Each eye acts as a camera and we capture two images of the same scene from two different viewpoints, that is, one image each using the left and right eyes. So, our brain takes these two images and builds a 3D map using stereo vision. This is what we want to achieve using stereo vision algorithms. We can capture two photos of the same scene using different viewpoints...
