Recovery of Nonrigid Curvilinear Objects Using Optical Flow

The kinetic depth effect which recognizes a 3-D structure from a 2-D information is explained from an algorithmic viewpoint among other human vision functions such as binocular vision. This paper proposes an algorithm for reconstructing the structure and motion of a 3-D nonrigid object using the information of positions and velocities in the time sequence of images. It is assumed that the nonrigid object does not deviate significantly from rigidity. First, the object is analyzed approximately by assuming that it is rigid. Then the first-order terms of Ct (which is an interval of two adjacent frames) are added to improve the approximation. Models of rigid and nonrigid objects were made, and information of their positions and optical flows were formed. The effectiveness of the proposed algorithm was confirmed by applying this to the data of the models.