Three-dimensional model-based object recognition and pose estimation using probabilistic principal surfaces

摘要

Abstract: A novel scheme using spherical manifolds is proposed for the simultaneous classification and pose estimation of 3D objects from 2D images. The spherical manifold imposes a local topological constraint on samples that are close to each other, while maintaining a global structure. Each node on the spherical manifold also corresponds nicely to a pose on a viewing sphere with 2 degrees of freedom. The proposed system is applied to aircraft classification and pose estimation.!16