A random sampling strategy for piecewise planar scene segmentation
Computer Vision and Image Understanding
Generalized Thin-Plate Spline Warps
International Journal of Computer Vision
Model-based plane-segmentation using optical flow and dominant plane
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Robust Algebraic Segmentation of Mixed Rigid-Body and Planar Motions from Two Views
International Journal of Computer Vision
Action recognition with appearance-motion features and fast search trees
Computer Vision and Image Understanding
Building facade detection, segmentation, and parameter estimation for mobile robot stereo vision
Image and Vision Computing
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We study and compare two novel embedding methods for segmenting feature points of piece-wise planar structures from two (uncalibrated) perspective images. We show that a set of different homographies can be embedded in different ways to a higher-dimensional real or complex space, so that each homography corresponds to either a complex bilinear form or a real quadratic form. Each embedding reveals different algebraic properties and relations of homographies. We give a closed-form segmentation solution for each case by utilizing these properties based on subspace-segmentation methods. These theoretical results show that one can intrinsically segment a piece-wise planar scene from 2-D images without explicitly performing any 3-D reconstruction. The resulting segmentation may make subsequent 3-D reconstruction much better-conditioned. We demonstrate the proposed methods with some convincing experimental results.