Research on 3D Reconstruction Method of Damaged Object Based on Neural Network

In everyday life, there are many objects that hold special meaning to us. Sometimes, these objects may become damaged due to various reasons. To repair and restore these damaged objects, a proposed method involves using a three-dimensional laser scanner to capture point cloud data of the damaged object. This point cloud data is then inputted into a neural network for repair and reconstruction, resulting in a three-dimensional reconstructed point cloud data. The final step involves using model encapsulation and 3D printing to create a highly accurate replica of the object. To validate this method, it was tested on reconstructing objects such as a cube, teapot, and gypsum statue. The research results demonstrate that the three-dimensional reconstructed models have clear texture, complete shape, and are highly consistent with the original objects, thus fulfilling the purpose of object restoration.