The essence of an image is a projection from a 3D scene onto a 2D plane, during which the depth information is lost. The 3D point corresponding to a specific image point is constrained to be on the line of sight. From a single image, it is very difficult to determine the depth information of various object points in an image. If two or more 2D images are used, then the relative depth point of the image points can be calculated which can be further used to reconstruct the 3D image by projecting the image points which includes the depth information as well. This paper presents two techniques namely binocular disparity and photometric stereo for depth calculation and 3D reconstruction of an object in an image as it requires minimum user intervention. …show more content…
These light sources are ideally point sources some distance away in different directions, so that in each case there is a well-defined light source direction from which to measure surface orientation. Therefore, the change of the intensities in the image depends on both local surface orientation and illumination direction.
Photometric stereo uses several images of the same surface under different illumination directions. The advantages of photometric stereo are: Unlike single image shape from shading algorithms, photometric stereo makes no assumption of the smoothness of the surface. It requires only additional lighting and can be easily implemented in at a reasonable computational cost. Each image brings along its own unique reflectance map, therefore each image will define a unique set of possible orientations for each point. Photometric stereo can recover not only surface orientation but also surface albedo.
4.2.1 Algorithm for photometric