EightPoints Algorithm(To find Essential Matrix and fundamental Matrix)
23 Mar 2022 | Visual SLAM
the EightPoint Algorithm is an algorithm used in computer vision to estimate the Essential matrix or the fundamental matrix related to a stereo camera from a set of corresponding image point.
use Sequence Quadratic Program(Gradient Newton, LM …) to solve unknown variable(Essential Matrix’s element) iterately.
eightpoints is selected by RANSAC
STEP
- image feature extraction
- image feature matching(KNN)
- use ransac outlier image feature matching’s result
- use ransac to find essential matrix and fundamental matrix with eight point algorithm.
- now with eesstianl matrix and intrinsic parameter to make fundamental matrix.
- and with fundamental matrix, using SVD to get Relative rotation Matrix and Traslation.(initialize pose)
- now we can generate 3d triangulation point by them
- and do PnP solve(3d - 2d) next camera pose estimation and literately generate 3d triangulation point(creating map) until camera frame no longer exist
Reference
https://www.quora.com/Computer-Vision-What-is-the-difference-between-the-essential-matrix-and-the-fundamental-matrix
https://www.baidu.com/from=844b/s?word=essential+matrix+c%2B%2B&sa=tb&ts=9943862&t_kt=0&ie=utf-8&rsv_t=c6b9XlTmpQPfwQGN%252BwmWZENzj0Tikfj9D2s6z%252BCpYp13qJVswX7UAlr6NA&ms=1&rsv_pq=12478331738706715542&ss=&rqlang=zh&oq=essential%2Bmatrix%E6%B1%82%E8%A7%A3
the EightPoint Algorithm is an algorithm used in computer vision to estimate the Essential matrix or the fundamental matrix related to a stereo camera from a set of corresponding image point.
use Sequence Quadratic Program(Gradient Newton, LM …) to solve unknown variable(Essential Matrix’s element) iterately.
eightpoints is selected by RANSAC
STEP
- image feature extraction
- image feature matching(KNN)
- use ransac outlier image feature matching’s result
- use ransac to find essential matrix and fundamental matrix with eight point algorithm.
- now with eesstianl matrix and intrinsic parameter to make fundamental matrix.
- and with fundamental matrix, using SVD to get Relative rotation Matrix and Traslation.(initialize pose)
- now we can generate 3d triangulation point by them
- and do PnP solve(3d - 2d) next camera pose estimation and literately generate 3d triangulation point(creating map) until camera frame no longer exist
Reference
https://www.quora.com/Computer-Vision-What-is-the-difference-between-the-essential-matrix-and-the-fundamental-matrix
https://www.baidu.com/from=844b/s?word=essential+matrix+c%2B%2B&sa=tb&ts=9943862&t_kt=0&ie=utf-8&rsv_t=c6b9XlTmpQPfwQGN%252BwmWZENzj0Tikfj9D2s6z%252BCpYp13qJVswX7UAlr6NA&ms=1&rsv_pq=12478331738706715542&ss=&rqlang=zh&oq=essential%2Bmatrix%E6%B1%82%E8%A7%A3
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