Title :
Algebraic functions for recognition
Author_Institution :
Artificial Intelligence Lab., MIT, Cambridge, MA, USA
fDate :
8/1/1995 12:00:00 AM
Abstract :
In the general case, a trilinear relationship between three perspective views is shown to exist. The trilinearity result is shown to be of much practical use in visual recognition by alignment-yielding a direct reprojection method that cuts through the computations of camera transformation, scene structure and epipolar geometry. Moreover, the direct method is linear and sets a new lower theoretical bound on the minimal number of points that are required for a linear solution for the task of reprojection. The proof of the central result may be of further interest as it demonstrates certain regularities across homographics of the plane and introduces new view invariants. Experiments on simulated and real image data were conducted, including a comparative analysis with epipolar intersection and the linear combination methods, with results indicating a greater degree of robustness in practice and a higher level of performance in reprojection tasks
Keywords :
algebra; image recognition; algebraic functions; alignment; direct reprojection method; epipolar intersection; homographics; perspective views; recognition; trilinear relationship; view invariants; visual recognition; Artificial intelligence; Biology computing; Cameras; Computational geometry; Image analysis; Laboratories; Layout; Performance analysis; Robustness; Solid modeling;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on