由LeNet-5从单张着装图像重建三维人体

Reconstruction of three-dimensional human bodies from single image by LeNet-5

提出基于LeNet-5的从单张着装图像恢复人体三维形状的方法,建立着装人体正面轮廓和人体形状空间之间的映射模型,实现了高效、精确的三维人体建模,可以应用于对人体表面形状精度要求较高的场合,如虚拟试衣.基于PGA在流型空间上对公开的三维人体数据集进行数据扩增,给虚拟人体进行着装,构建着装人体数据库.从着装人体正面投影图像中提取信息,以人体形状参数及正、侧面轮廓信息为约束,基于LeNet-5完成三维人体重建.实验证明,对于身穿不同款式服装的人,采用的模型通常都能从单张着装图像中重建得到较高精度的三维人体模型.

A novel human body modeling method that can reconstruct three-dimensional(3D)human bodies from single dressed human body image based on LeNet-5 was proposed.The method can reconstruct 3D human bodies accurately and efficiently,and the reconstruction results can be potentially used in some occasions where require precise surface shapes,such as virtual try-on systems.3D human bodies collected from open datasets were selected and augmented on manifolds with PGA.A dressed human body database was established after dressing these 3D human bodies with virtual garments in various types and sizes.Feature descriptors were extracted from the frontal projected images of dressed human bodies.The corresponding 3D human bodies were constructed through LeNet-5 with the constraints of shape parameters as well as the frontal and lateral contours.The experimental results show that the model can reconstruct a high-precision 3D human body from a single dressed human body image for people wearing different styles of clothing.