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Abstract

The present invention discloses a non-feature extraction dense SFM three-dimensional reconstruction method, comprising: inputting n images about a certain scenario, n≧2; establishing a world coordinate system consistent with a certain camera coordinate system; constructing an objective function similar to optical flow estimation by taking a depth of a three-dimensional scenario and a camera projection matrix as variables; employing a from coarse to fine pyramid method; designing an iterative algorithm to optimize the objective function; outputting depth representing the three-dimensional information of the scenario and a camera projection matrix representing relative location and pose information of the camera; and realizing dense projective, similarity or Euclidean reconstruction according to the depth representing the three-dimensional information of the scenario. The present invention can accomplish dense SFM three-dimensional reconstruction with one step. Since estimation of dense three-dimensional information is achieved by one-step optimization, an optimal solution or at least local optimal solution can be obtained by using the objective function as an index, it is significantly improved over an existing method and has been preliminarily verified by experiments.

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First Claim