Linear motion estimation for systems of articulated planes

In this paper, we describe the explicit application of articulation constraints for estimating the motion of a system of planes. We relate articulations to the relative homography between planes and show that for affine cameras, these articulations translate into linear equality constraints on a linear least squares system, yielding accurate and numerically stable estimates of motion. The global nature of motion estimation allows us to handle areas where there is limited texture information and areas that leave the field of view. Our results demonstrate the accuracy of the algorithm in a variety of cases such as human body tracking, motion estimation of rigid, piecewise planar scenes and motion estimation of triangulated meshes.

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