Stereoscopic visualization of monocular images in photo collections

In this paper we propose a novel approach for 3D video/photo visualization using an ordinary digital camera. The idea is to turn any 2D camera into 3D based on the data derived from a collection of captured photos or a recorded video. For a given monocular input, the retrieved information from the overlapping photos can be used to provide required information for performing 3D output. Robust feature detection and matching between images is hired to find the transformation between overlapping frames. The transformation matrix will map images to the same horizontal baseline. Afterwards, the projected images will be adjusted to the stereoscopic model. Finally, stereo views will be coded into 3D channels for visualization. This approach enables us making 3D output using randomly taken photos of a scene or a recorded video. Our system receives 2D monocular input and provides double layer coded 3D output. Depending on the coding technology different low cost 3D glasses will be used for viewers.