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郁闷的GENIUS

金虫 (小有名气)

[求助] 大家讨论下如何通过一组图像序列求取相机的移动轨迹啊? 已有1人参与

RT,小弟看了些论文,但过程讲的都不是很清楚,想请大神帮忙解答下:当两张图像的匹配点对求出来后,如何计算拍摄这两张图像时相机的相对位姿呢?
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lxc_422

新虫 (小有名气)

【答案】应助回帖

I suggest you to add your question into the BBS.
It make others can read it, maybe this could help them while encountering the similar problem.
全心用于科研,不能有丝毫松懈。学术是主题,创新是生命。
5楼2014-12-25 12:55:57
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lxc_422

新虫 (小有名气)

【答案】应助回帖

★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★
感谢参与,应助指数 +1
郁闷的GENIUS: 金币+5, ★★★很有帮助 2014-12-25 11:42:00
郁闷的GENIUS: 金币+10 2014-12-25 18:12:01
郁闷的GENIUS: 金币+10 2015-01-03 17:33:40
First, you should compute the essential matrix E.
Second, according to E=[t]xR, if you know the translation matrix t and the rotation matrix R, then you could obtain the pose of the camera.
However, you only have two images at hand. We assume that the camera are uncalibrated, therefore, you need to solve the fundamental matrix F from the corresponding points.
Since E=KT*F*K, you should compute the calibration matrix K. We know that K only could be determined from autocalibration(or self-calibration), because the camera has not been calibrated.
Hence, if you solved the problem of camera autocalibration and obtained K, then you could easily obtain the pose of the camera.
How could we solve the autocalibration problem? The idea of auto calibrating a camera originated in the literature titled "Camera self-calibration: Theory and experiments" by Faugeras, Luong and Maybank in 1992.
You could find out more useful information from this idea.
全心用于科研,不能有丝毫松懈。学术是主题,创新是生命。
2楼2014-12-25 10:09:32
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郁闷的GENIUS

金虫 (小有名气)

引用回帖:
2楼: Originally posted by lxc_422 at 2014-12-25 10:09:32
First, you should compute the essential matrix E.
Second, according to E=xR, if you know the translation matrix t and the rotation matrix R, then you could obtain the pose of the camera.
However,  ...

非常感谢,如果先用张正友的方法将相机标定好,并得到了相关参数,是不是只要通过两张图像的匹配点对求本质矩阵E就可以了?
3楼2014-12-25 11:41:48
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lxc_422

新虫 (小有名气)

【答案】应助回帖

Yes, you are right!
If you used Zhang's method to obtain the interal parameters of the camera(i.e. the calibration matrix K), then it is simple to solve this problem.
全心用于科研,不能有丝毫松懈。学术是主题,创新是生命。
4楼2014-12-25 12:50:37
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