Keyframe-Based Texture Mapping for RGBD Human Reconstruction

Realistic human model has a wide range of requirements in 3D content creation. A model with high-quality texture map can display human body surface details in low facets which could be toughly represented by geometric mesh. Image-based texture mapping suffers from discontinuities due to geometry inaccuracy, camera pose drifts, and illumination changes. In this paper, we propose a keyframe-based texture map generation method to obtain more desired texture mapping results. Our method firstly acquire the keyframes by performing a spatio-temporal sampling strategy, rather than just sampling keyframes according to time interval. Then, we apply an efficient patch-based optimization to the keyframes to make the texture data in different views alinged with each other. Finally, we generate a texture atlas from the aligned texture and the simplified mesh. Experimental results demonstrate that our method can get realistic human models with low facets and competitive details within short minutes.