Robust Computer Vision Techniques for High-quality 3D Modeling

被引:0
|
作者
Lee, Joon-Young [1 ]
Jung, Jiyoung [1 ]
Bok, Yunsu [1 ]
Park, Jaesik [1 ]
Choi, Dong-Geol [1 ]
Han, Yudeog [1 ]
Kweon, In So [1 ]
机构
[1] Korea Adv Inst Sci & Technol, Robot & Comp Vis Lab, Seoul, South Korea
关键词
PHOTOMETRIC STEREO; SCENES;
D O I
10.1109/ACPR.2013.215
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we present our recent sensor fusion approaches to obtain high-quality 31) information. We first discuss two fusion methods that combine geometric and photometric information. The first method, multiview photometric stereo, reconstructs the full 3D shape of a target object. The geometric and photometric information is efficiently fused by using a planar mesh representation. The second method performing shape-from-shading with a Kinect sensor estimates the shape of an object under uncalibrated natural illumination. Since the method uses a single RGB-D input, it is capable of capturing the high quality shape details of a dynamic object under varying illumination. Subsequently, we summarize a calibration algorithm of a time-of-flight (ToF) sensor and a camera fusion system with a 2.51) pattern. Lastly, we present a camera-laser sensor fusion system for the large-scale 31) reconstruction.
引用
收藏
页码:6 / 10
页数:5
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