A Spatial-temporal Multiplexing Method for Dense 3D Surface Reconstruction of Moving Objects

Abstract

Three-dimensional reconstruction of dynamic objects is important for robotic applications, for example, the robotic recognition and manipulation. In this paper, we present a novel 3D surface reconstruction method for moving objects. The proposed method combines the spatial-multiplexing and time-multiplexing structured-light techniques that have advantages of less image acquisition time and accurate 3D reconstruction, respectively. A set of spatial-temporal encoded patterns are designed, where a spatial-encoded texture map is embedded into the temporal-encoded three-step phase-shifting fringes. The specifically designed spatial-coded texture assigns high-uniqueness codeword to any window on the image which helps to eliminate the phase ambiguity. In addition, the texture is robust to noise and image blur. Combining this texture with high-frequency phase-shifting fringes, high reconstruction accuracy would be ensured. This method only requires 3 patterns to uniquely encode a surface, which facilitates the fast image acquisition for each reconstruction step. A filtering stereo matching algorithm is proposed for the spatial-temporal multiplexing method to improve the matching reliability. Moreover, the reconstruction precision is further enhanced by a correspondence refinement algorithm. Experiments validate the performance of the proposed method including the high accuracy, the robustness to noise and the ability to reconstruct moving objects.