Multi-View Stereo Network with Gaussian Distribution Iteration
نویسندگان
چکیده
Multi-view stereo estimates the depth maps of multiple perspective images in a scene and then fuses them to generate 3D point cloud scene, which is an essential technology reconstruction. In this paper, we propose deep learning method GDINet, applying probabilistic methods pyramid framework, can significantly improve reconstruction quality. detail, first establish Gaussian distribution for each image’s pixel iterate it framework. The mean value estimated depth, variance represents estimation error. addition, design novel loss function with excellent convergence train our network. Finally, present initialization module coarse distribution, controlling parameters reasonable range. Our results rank $2nd$ on both DTU Tanks & Temples datasets, showing that network has high accuracy, completeness, robustness. We also make visualization comparison BlendedMVS dataset (containing many aerial images) demonstrate generalization ability model.
منابع مشابه
User Directed Multi-view-stereo
Depth reconstruction from video footage and image collections is a fundamental part of many modelling and image-based rendering applications. However real-world scenes often contain limited texture information, repeated elements and other ambiguities which remain challenging for fully automatic algorithms. This paper presents a technique that combines intuitive user constraints with dense multi...
متن کاملMulti - View Stereo Reconstruction Technique
3D modeling of complex objects is an important task of computer graphics and poses substantial difficulties to traditional synthetic modeling approaches. The multi-view stereo reconstruction technique, which tries to automatically acquire object models from multiple photographs, provides an attractive alternative. The whole reconstruction process of the multi-view stereo technique is introduced...
متن کاملHallucination-Free Multi-View Stereo
We present a multi-view stereo method that avoids producing hallucinated surfaces which do not correspond to real surfaces. Our approach to 3D reconstruction is based on the minimal s-t cut of the graph derived from the Delaunay tetrahedralization of a dense 3D point cloud, which produces water-tight meshes. This is often a desirable property but it hallucinates surfaces in complicated scenes w...
متن کاملConsensus Multi-View Photometric Stereo
We propose a multi-view photometric stereo technique that uses photometric normal consistency to jointly estimate surface position and orientation. The underlying scene representation is based on oriented points, yielding more flexibility compared to smoothly varying surfaces. We demonstrate that the often employed least squares error of the Lambertian image formation model fails for wide-basel...
متن کاملSegmentation based Multi-View Stereo
This paper presents a segmentation based multiview stereo reconstruction method. We address (i) dealing with uninformative texture in very homogeneous image areas and (ii) processing of large images in affordable time. To avoid searching for optimal surface position and orientation based on uninformative texture, we (over)segment images into segments of low variation of color and intensity and ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2023
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2023.3280929