PatchMatch based Multiview Stereo with Local Quadric Window
Hyewon Song, Jae‐Seong Park, Suwoong Heo, Jiwoo Kang, Sanghoon Lee · 2020
Although various stereo matching methods are studied in many years, the accurate 3D reconstruction from multiview stereos in high-fidelity is still challenging due to the surface inconsistency caused by various factors such as specular illumination. In this paper, we propose an accurate PatchMatch based multiview stereo matching method with a quadric support window that efficiently captures the surface of a complex structured object. Our method takes three novel contributions. Firstly, delicate surface configurations are used for representing the complex structure of an object. By using a general 3D quadric function, the structured object surfaces can be estimated more accurately. In addition, an illumination robust framework is proposed, where the patch dissimilarities are precisely measured with disentangled representation. The matching cost is defined based on disentangled measurements of the object photometric and geometric properties, balancing the pixel intensities between images robust to illumination. Lastly, a multiview propagation method is proposed to confirm shape consistency among views. Through the disparity refinement to unify plane parameters of the views, the object surface is estimated from a global perspective. Consequently, the dense and smooth 3D shape of the object is reconstructed accurately. We evaluate our proposed method on the Middlebury stereo set and conduct comprehensive experiments on facial images. Both quantitative and qualitative results demonstrate that the proposed method shows significant improvements over state-of-the-art methods.