Shape recovery of rotating object using weighted voting of spacio-temporal images

We propose a method to recover the 3D shape of an object rotating on a turnable. A spacio-temporal image is made of the sequential images taken by a single camera. Then, the trajectories which correspond to the 3D points on the surface are extracted in the spacio-temporal image by using "weighted voting" of all intensity values on a constrained surface. Since the method consequently utilize intensity information as it is, the method can recover dense 3D positions compared with the one using feature extraction and tracking. Also, it can recover concave shapes unlike the one using silhouettes of the object. The experimental results with real images show the effectiveness of our method.