A single-image human body reconstruction method combining normal recovery and frequency domain completion

Reconstructing a 3D human body from a single image is convenient and efficient, but it faces challenges when the face is heavily occluded or the person is wearing loose clothing. In this paper, we propose a frequency domain-based method for completing missing parts of the human body using manifold harmonics and frequency domain analysis. Our approach involves linear interpolation of the incomplete 3D human body obtained through normal integration. The interpolated points are then projected onto the appropriate dimension of the frequency domain space using manifold harmonic bases. Through Laplacian mesh editing, the interpolated points are replaced, resulting in a refined and complete 3D human body. Our method surpasses the limitations of template human bodies and marching cubes algorithms, enabling more detailed feature reconstruction. By locally completing the body in a low-dimensional frequency domain space, our method avoids over smoothing and bulging issues, effectively filling the missing regions while maintaining mesh smoothness consistency. Experimental results demonstrate the effectiveness and superiority of our frequency domain-based completion method for accurate and detailed 3D human body reconstruction from single images.