With the three-dimensional (3D) coordinates of objects captured by a sequence of images taken in different views, object reconstruction is a technique which aims to recover the shape and appearance information of objects. Although great progress in object reconstruction has been made over the past few years, object reconstruction in occlusion situations remains a challenging problem. In this paper, we propose a novel method to reconstruct occluded objects based on synthetic aperture imaging. Unlike most existing methods, which either assume that there is no occlusion in the scene or remove the occlusion from the reconstructed result, our method uses the characteristics of synthetic aperture imaging that can effectively reduce the influence of occlusion to reconstruct the scene with occlusion. The proposed method labels occlusion pixels according to variance and reconstructs the 3D point cloud based on synthetic aperture imaging. Accuracies of the point cloud are tested by calculating the spatial difference between occlusion and non-occlusion conditions. The experiment results show that the proposed method can handle the occluded situation well and demonstrates a promising performance.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386989PMC
http://dx.doi.org/10.3390/s19030607DOI Listing

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