The need for camera calibration has been a
fundamental requirement since the foundation of
photogrammetry. As the number of photogrammetry
applications grows and the technology advances, camera
calibration became more complex to undertake.
However, when measurements derived from the imagery
is used for scene modelling purposes, the consequences of
small imaging errors can be significant on the accuracy
of derived models. Thus, the development of cheaper
lenses such as those of consumer grade cameras and
their integration in the Photogrammetry process
requires from camera calibration approaches to
accurately model the projection process from the 3D
scene onto the 2D image plan and also offer robust
solutions to derive with high accuracy the various
camera parameters. Several line based and points based
camera calibration methods have been proposed in
literature and reported producing promising results but
the majority of such approaches were found either
numerically instable or suffer from serious limitations
when it comes to removing distortions at the edges of
imagery. The fact that these techniques rely of the
traditional brown’s model which assumes symmetric
radial distortions make them no suitable for consumer
grade digital cameras which are known for their instable
internal geometry. This study found undisputable that
new analytical camera calibration techniques more
adapted to the internal geometry of consumer grade
cameras are needed.