A high-precision linear method for camera pose determination

2010 ◽  
Author(s):  
Sen Yang
Keyword(s):  
High Precision ◽  
Linear Method ◽  
Pose Determination ◽  
Camera Pose

scholarly journals A robust and accurate camera pose determination method based on geometric optimization search using Internet of Things

2019 ◽  
Vol 15 (6) ◽  
pp. 155014771985758
Author(s):  
Qi Wang ◽  
Zhangyan Zhao ◽  
Enshun Lu ◽  
Yang Liu ◽  
Licheng Liu
Keyword(s):  
Internet Of Things ◽  
Error Function ◽  
Uncertain Data ◽  
Real Data ◽  
Geometric Optimization ◽  
Determination Method ◽  
Pose Determination ◽  
Camera Pose ◽  
Optimization Search ◽  
Internet Of Things Technology

We propose a robust and accurate camera pose determination method based on geometric optimization search using the Internet of Things (IoT). The central idea is to (1) obtain image information through Internet of Things technology, (2) obtain the first pose by minimizing the error function, and (3) use the geometric relationship and constraint condition to obtain the appropriate attitude angles as a new initial value for the next iteration calculation. The features of this method are as follows. First, this method can deal with a large amount of uncertain data, such as in the case of any shooting angle, in the case of any reference point, and in the case of a small number of feature points. Finally, because of using Internet of Things technology, our method can quickly complete data processing and transmission. Compared to state-of-the-art methods, the experimental results show that our approach performs well on both synthetic and real data and can be used to provide accurate and stable data for subsequent applications.

Camera Pose Determination and 3-D Measurement From Monocular Oblique Images With Horizontal Right Angle Constraints

2014 ◽  
Vol 11 (11) ◽  
pp. 1976-1980 ◽  
Author(s):  
Xiaodong Xiong ◽  
Yongjun Zhang ◽  
Junfeng Zhu ◽  
Maoteng Zheng
Keyword(s):  
Pose Determination ◽  
Camera Pose ◽  
Oblique Images

Automatic measurement of SAED patterns from asbestos minerals

1988 ◽  
Vol 46 ◽  
pp. 846-847
Author(s):  
J. C. Russ ◽  
T. Taguchi ◽  
P. M. Peters ◽  
E. Chatfield ◽  
J. C. Russ ◽  
...  
Keyword(s):  
Diffraction Pattern ◽  
High Precision ◽  
Diffraction Data ◽  
Automatic Measurement ◽  
Automatic Method ◽  
Important Method ◽  
X Ray ◽  
Integrated Intensity ◽  
Asbestiform Minerals ◽  
True Center

Conventional SAD patterns as obtained in the TEM present difficulties for identification of materials such as asbestiform minerals, although diffraction data is considered to be an important method for making this purpose. The preferred orientation of the fibers and the spotty patterns that are obtained do not readily lend themselves to measurement of the integrated intensity values for each d-spacing, and even the d-spacings may be hard to determine precisely because the true center location for the broken rings requires estimation. We have implemented an automatic method for diffraction pattern measurement to overcome these problems. It automatically locates the center of patterns with high precision, measures the radius of each ring of spots in the pattern, and integrates the density of spots in that ring. The resulting spectrum of intensity vs. radius is then used just as a conventional X-ray diffractometer scan would be, to locate peaks and produce a list of d,I values suitable for search/match comparison to known or expected phases.

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