使用单一运动的类Kinect深度相机重建和优化静态3D全身人体模型.首先针对类Kinect深度相机产生噪声原因提出一种降噪处理方法进行降噪.结合深度信息和RGB信息获取匹配块,使用高斯混合模型进行局部配准和逐层封闭曲线拟合方法进行全局配准,结合改进方向距离函数进行合并,最后使用泊松表面重建方法获取三维模型.实验结果表明,该方法能够重建出较高精度的三维人体模型.

This paper presents an approach to reconstruct and optimize static 3D human body models using a single Kinect-like motion depth camera by moving the sensor freely around the human body. First, to reduce the noise in the depth data captured by the Kinect-like depth sensor, an approach is proposed to filter it according to the noise source created from the Kinect-like depth sensor. Then, the search for the corresponding patch is performed by combining with the information of depth and RGB, and the pair frames are aligned with the Gaussian mixture model and the improved signed distance function. For the loop closure problem, a closed curve fitting based method is provided with different layers to globally register all the frames. Finally, the human body surface is constructed by using the Poisson reconstruction. Experimental results show that the presented approach can reconstruct human models with high quality.

国家自然科学基金(61272298, 61133009);浙江省自然科学基金(LY14A010032);国家教育部留学回国人员科研启动基金([2009]1590);浙江理工大学521人才资助项目