Inferring both 3D structure and motion of nonrigid objects from monocular images is an important problem in computational vision. The challenges stem not only from the absence of ...
We propose a new method for recovering a 3-D object shape from an image sequence. In order to recover high-resolution relative depth without using the complex Markov random field...
Non-rigid structure from motion (NR-SFM) is a difficult, underconstrained problem in computer vision. This paper proposes a new algorithm that revises the standard matrix factori...
We consider the problem of nonrigid shape and motion recovery from point correspondences in multiple perspective views. It is well known that the constraints among multiple views o...
Estimating the structure of the human face is a long studied and difficult task. In this paper we present a new method for estimating facial structure from only a minimal number o...
Nathan Faggian, Andrew P. Paplinski, Jamie Sherrah