3D positioning of physical body points plays an important role in machine vision applications involving feature extractions

pattern recognition

geometrical measurement and motion analysis. To cover a wide detection and mitigate the influence of occlusion some multiple view technique for positioning is adopted

a technique that is generally fulfilled using expensive instruments and specialized software and thus its applications are restricted in terms of number of points that can be positioned simultaneously

ability for user programming and affordability. With both complete algorithm and procedure

this paper propose a DLT(Direct Linear Transformation)-based method for 3D positioning of object point in the world coordinate frame via multiple view geometry

applicable to multiple view provided by either a single camera moving into different positions for still scene positioning

or by multiple cameras for a dynamic positioning application. Method：This method consists of 2 main steps

i.e. a DLT-based camera calibration and a 3D coordinates reconstruction (positioning) with the camera parameters obtained in calibration. In the calibration step

a minimum of 6 control points

not co-planar but with known world coordinates

are set up and linear equations are formulated modeling relationship between world frame coordinates of these control points and their relevant image points position in the camera coordinate frame

and equations then are solved via least squares method for best linear estimation of the camera parameters in the form of a series of L intermediary parameters. In the positioning step

the concept of finding intersection point of multiple spatial ray - each ray emanating form the corresponding cameras optical center and the image point corresponding to the same physical point is used to formulate equations for the 3D positioning

which than are solved also via the linear least square method with the obtained L parameters. Still scene physical point positioning tests of 10 control points and 20 test points are conducted on a field leveler machine platform

where the scene is captured by one camera in 3 different positions and true reference positions of the test points provided by a total station. Result: Results show that the average absolute error of the coordinates measured in the X

Y and Z directions is 4.19mm

3.97mm

3.69mm

and the spatial relative distance error is 0.81%

thus satisfying the needs of general geometrical measurement. Conclusion: The method proposed can measure static and dynamic 3D world coordinates for multiple physical points

though higher via a more complicated DLT-based calibration procedure for the additional cameras distortion parameters.