用飞行时间相机优化可视外壳的实时三维重建算法

摘要

在基于图像的三维重建领域中,基于轮廓或立体匹配的实时三维重建算法精度很低,而高精度的三维重建算法需要像素级能量最优化,很难做到实时.针对这个问题,提出一种用飞行时间相机拍摄得到的深度图优化可视外壳方法的实时三维重建算法.首先使用一种简化的深度标定方法对深度数据进行误差修正；然后根据两种相机得到的数据构造粗糙网格模型；最后进行局部搜索匹配,对模型表面进行像素块的优化.实验结果表明,该算法比同类算法的实时性高,且能够有效地处理模型表面的凹多边形,比可视外壳算法的精度有较大改善.%In the field of image-based 3D reconstruction, real-time reconstruction approaches based on silhouette or stereo suffered from lacking of details. On the other hand, reconstruction algorithms with high quality need pixel-level energy optimization, which leads to relatively low performance. Based on those problems, this paper presents a real-time 3D reconstruction algorithm, which based on visual hull refined by depth map from time of flight(TOF) sensor. First, the depth data from TOF sensor is refined by a simplified depth calibration method. A fusion approach using both foreground silhouette and depth data is applied to recover an initial coarse model. Finally the model is refined by a local stereo-matching search. Our experiments illustrate that this algorithm is more efficient than heterogeneous cameras-based algorithms in improving the reconstruction quality similar, and the concaves can be recovered effectively.