关键词: 人体重建, 虚拟标记, 多视图融合, 点云对齐, 人体测量

Abstract: 3D human body reconstruction technology had developed rapidly. However, when the body part was occluded, the performance of the single-view human body reconstruction method would decline significantly；the multi-view approach offered better accuracy, but it was faced with challenges in effectively combining data from different views. To achieve this issue, a multi-view fusion strategy based on Virtual Marker (VM) was introduced. First, extract Virtual Marker from the image and utilize the characteristics of VM to ensure the shape accuracy of the human body; Secondly, point cloud registration was used to align the markers from different views, this process was based on confidence, ensuring that a clear perspective has a higher impact on the final result; Finally, weighted interpolation was utilized to complete the entire reconstruction process from the markers to the three-dimensional human body. The proposed method reduces computational costs, avoids common problems such as feature matching and viewpoint alignment, and also handles occlusion better than the single-view method. On the public dataset Human3.6m, the Mean Per-Joint Position Error (MPJPE) metric has increased by 22% and 12% respectively compared with the POTTER (Pooling Attention Transformer for Efficient Human Mesh Recovery) and FeatER (Feature Map-Based TransformER) methods. When applied to body size measurements on the collected dataset, the average error of all dimensions remained below 0.85 cm. 

Key words: human body reconstruction, Virtual Marker (VM), muti-view fusion, point cloud alignment, human body measurement