Indirect decoding edges for one-shot shape acquisition

Determining the correspondence in coded structured light is challenging, but it is very important in one-shot techniques for 3D shape reconstruction. The problem of decoding stripe patterns can be modeled as matching two code sequences. We propose decoding edges indirectly based on the property of the stripe pattern, which can be represented as edge code, color code, or mixed code sequences. While traditional methods match two edge code sequences, indirect decoding matches two color sequences or mixed code sequences. The advantages of the proposed method, including a higher Hamming distance, enforced local coherence, and more code information, make indirect decoding excellent in performance. Previously, the lack of ground truth has prevented direct comparisons of different decoding algorithms. Here we obtain six benchmark datasets using the robust space-time analysis. Five decoding methods are quantitatively evaluated using the ground truth. The comparison results show that our method is robust for complex code situations and that it outperforms the state-of-the-art technique in this area.