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We propose a novel geometric Rao-Blackwellized particle filtering framework for monocular SLAM with locally planar landmarks. We represent the states for the camera pose and the landmark plane normal as SE(3) and SO(3), respectively, which are both Lie groups. The measurement error is also represented as another Lie group SL(3) corresponding to the space of homography matrices. We then formulate the...
We propose a geometric method for visual tracking, in which the 2-D affine motion of a given object template is estimated in a video sequence by means of coordinate-invariant particle filtering on the 2-D affine group Aff(2). Tracking performance is further enhanced through a geometrically defined optimal importance function, obtained explicitly via Taylor expansion of a principal component analysis...
We propose a particle filtering-based visual tracker, in which the affine group is treated as the state. We first develop a general particle filtering algorithm that explicitly takes into account the geometry of the affine group. The tracking performance is further enhanced by the geometric auto-regressive process used for the state dynamics, combined state-covariance estimation, and robust measurement...
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