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If I have been given multiple view images having known orientation parameters, then from a selected image line segment (corresponding line segments from each image) how could I compute a line 3D in object space?

as I am looking for an accurate one single line 3d, I want to use least square theories.

As a starting point, I wish to use viewing planes which contains coordinate of principle point and normal vectors of each viewing plane. So, that the problem can be considered as a plane intersection leading to a line 3d.

Note: These viewing planes are given by viewing rays. So each line segment in the image make one viewing plane.

any assistant on this least square process.

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What is the format of the orientation information you have for each image ? Do you use a pinhole camera model ? –  Vincent Nivoliers Mar 25 '13 at 21:37
    
@Vincent Nivoliers: honestly, I dont know that much. What I have is viewing planes taken from viewing rays. anyhow, i have updated the post. i guess now it can be undesrtood. –  gnp Mar 25 '13 at 21:57

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Generally, you're talking about "image-based modeling", typically recovering lines and features based on multiple images.

The first I saw about this was Paul Debevec's work when I was at Berkeley. His Campanile movie is still a thing of beauty.

More broadly, you have to worry about uncertainty of the position and orientation of the image -- I've dealt with this in medical imaging using orthogonal imaging, but it required manual registration. Here's at least one stab at the general problem of line matching.

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