This paper presents an effective method for generating a spatiotemporal (time-varying) texture map for a dynamic object using a single RGB-D camera. The input of our framework is a 3D template model and an RGB-D image sequence. Since there are invisible areas of the object at a frame in a single-camera setup, textures of such areas need to be borrowed from other frames. We formulate the problem as an MRF optimization and define cost functions to reconstruct a plausible spatiotemporal texture for a dynamic object. Experimental results demonstrate that our spatiotemporal textures can reproduce the active appearances of captured objects better than approaches using a single texture map.
@article{arxiv.2108.09007,
title = {Spatiotemporal Texture Reconstruction for Dynamic Objects Using a Single RGB-D Camera},
author = {Hyomin Kim and Jungeon Kim and Hyeonseo Nam and Jaesik Park and Seungyong Lee},
journal= {arXiv preprint arXiv:2108.09007},
year = {2021}
}