论文标题
使用智能手机视频捕获高精度的面部几何形状
High Accuracy Face Geometry Capture using a Smartphone Video
论文作者
论文摘要
坐在桌子上时可以获得的最准确的3D型号是什么？我们试图在我们的工作中回答这个问题。到目前为止，高保真面部的重建仅限于工作室设置或昂贵的3D扫描仪。另一方面，不受约束的重建方法通常受到低容量模型的限制。我们的方法使用智能手机在不受约束的环境中使用智能手机拍摄的视频拍摄来重建对象的准确面部几何形状。我们的方法利用了视觉猛击，关键点检测和对象检测的最新进展，以提高准确性和鲁棒性。通过不受限制为模型子空间，我们的重建网格捕获了重要的细节，同时又对噪声稳健并在拓扑上保持一致。我们的评估表明，我们的方法在几何精度和捕获特定于人的细节方面都超过了当前的单一和多视图基准，这对于使外观现实的模型很重要。
What's the most accurate 3D model of your face you can obtain while sitting at your desk? We attempt to answer this question in our work. High fidelity face reconstructions have so far been limited to either studio settings or through expensive 3D scanners. On the other hand, unconstrained reconstruction methods are typically limited by low-capacity models. Our method reconstructs accurate face geometry of a subject using a video shot from a smartphone in an unconstrained environment. Our approach takes advantage of recent advances in visual SLAM, keypoint detection, and object detection to improve accuracy and robustness. By not being constrained to a model subspace, our reconstructed meshes capture important details while being robust to noise and being topologically consistent. Our evaluations show that our method outperforms current single and multi-view baselines by a significant margin, both in terms of geometric accuracy and in capturing person-specific details important for making realistic looking models.
