Visual methods for three-dimensional modeling
Most animals use vision as a primary sensor to interact with their environment. Navigation or manipulation of objects are among the tasks that can be better achieved while understanding the three-dimensional structure of the scene. 
In this thesis, we present a variety of computational techniques for estimating 3D shape from 2D images, based on both passive and active technologies. 
The first proposed method is purely passive. In this technique, a single camera is moved in an unconstrained manner around the scene to model as it acquires a sequence of images. The reconstruction process consists then of retrieving the trajectory of the camera, as well as the 3D structure of the scene using only the information contained in the images. 
The second method is based on active lighting technology. In the philosophy of standard 3D scanning methods, a projector is used to project light patterns in the scene. The shape of the scene is then inferred from the way the patterns deform on the objects. The main novelty of our scheme compared to traditional methods is in the nature of the patterns, and the type of image processing associated to them. Instead of using standard binary patterns made out of black and white stripes, our scheme uses a sequence of grayscale patterns with a sinusoidal profile in brightness intensity. This choice allows us to establish correspondence (between camera image, and projector image) in a dense fashion, leading to depth computation at (almost) every pixel in the image. 
The last reconstruction method that we propose in this thesis is an alternative 3D scanning scheme that does not require any other device besides a camera. The main idea is to substitute the projector by a standard light source (such as a desk lamp), and use a pencil (or any other object with a straight edge) to cast planar shadows in the scene. The 3D geometry of the scene is then inferred from the way the shadow naturally deforms on the objects in the scene. Since this technology is largely inspired from structured lighting techniques, we call it ‘weakly structured lighting.’