CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 1997 vol.19 Issue No.03 - March
Issue No.03 - March (1997 vol.19)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.584098
<p><b>Abstract</b>—The factorization method, first developed by Tomasi and Kanade, recovers both the shape of an object and its motion from a sequence of images, using many images and tracking many feature points to obtain highly redundant feature position information. The method robustly processes the feature trajectory information using singular value decomposition (SVD), taking advantage of the linear algebraic properties of orthographic projection. However, an orthographic formulation limits the range of motions the method can accommodate. Paraperspective projection, first introduced by Ohta, is a projection model that closely approximates perspective projection by modeling several effects not modeled under orthographic projection, while retaining linear algebraic properties. Our paraperspective factorization method can be applied to a much wider range of motion scenarios, including image sequences containing motion toward the camera and aerial image sequences of terrain taken from a low-altitude airplane.</p>
Motion analysis, shape recovery, factorization method, three-dimensional vision, image sequence analysis, singular value decomposition.
Conrad J. Poelman, "A Paraperspective Factorization Method for Shape and Motion Recovery", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.19, no. 3, pp. 206-218, March 1997, doi:10.1109/34.584098