Egomotion Estimation Using Quadruples of Collinear Image Points

This paper considers a fundamental problem in visual motion perception, namely the problem of egomotion estimation based on visual input. Many of the existing techniques for solving this problem rely on restrictive assumptions regarding the observer's motion or even the scene structure. Moreover, they often resort to searching the high dimensional space of possible solutions, a strategy which might be inefficient in terms of computational complexity and exhibit convergence problems if the search is initiated far away from the correct solution. In this work, a novel linear constraint that involves quantities that depend on the egomotion parameters is developed. The constraint is defined in terms of the optical flow vectors pertaining to four collinear image points and is applicable regardless of the egomotion or the scene structure. In addition, it is exact in the sense that no approximations are made for deriving it. Combined with robust linear regression techniques, the constrain...

• Type: Conference
• Year: 2000
• Where: ECCV
• Authors: Manolis I. A. Lourakis
• Keywords: Computer Vision, ECCV 2000, Motion Parameters, Optical Flow Fields, Optical Flow Vectors, Robust Linear Regression, Visual Motion Perception