Tenth International Conference on Machine Vision (ICMV 2017) 2018
DOI: 10.1117/12.2310111
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The method for homography estimation between two planes based on lines and points

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Cited by 4 publications
(3 citation statements)
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“…For this purpose, let us take the coordinate system of the polychromatic projection as the basic one, and for the projections from the reflections, we search for the parameters of the geometric transformation relative to the polychromatic projection. In our optical scheme, straight lines are transformed into straight lines without bending, so the distortion of images is described by the projective transformation [ 41 ]. The projective transformation , in homogeneous coordinates, maps a point to a point ( and is given in the form: …”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…For this purpose, let us take the coordinate system of the polychromatic projection as the basic one, and for the projections from the reflections, we search for the parameters of the geometric transformation relative to the polychromatic projection. In our optical scheme, straight lines are transformed into straight lines without bending, so the distortion of images is described by the projective transformation [ 41 ]. The projective transformation , in homogeneous coordinates, maps a point to a point ( and is given in the form: …”
Section: Methodsmentioning
confidence: 99%
“…Since each point has two coordinates, the system of linear equations built on 4 points will find 8 unknown parameters. For the system to be nonsingular, no three points must lie on the same line [ 41 ].…”
Section: Methodsmentioning
confidence: 99%
“…The general scheme of the proposed decisionmaking algorithm is shown in the next paragraph in the form of pseudocode. Here, the algorithm receives as input a sequence of projectively corrected images of the document (the projective image is achieved using specialized algorithms such as [20,21]) and the results of recognition of all specified attributes on each image. Each such result contains the coordinates of the text field bounding rectangle (for more information on this topic, see [22]), the field recognition result, and the neural network's confidence in its answer.…”
Section: Algorithm For Choosing the Best Framementioning
confidence: 99%