  Camera calibration is a crucial step in robotics and computer vision.
Accurate camera parameters are necessary to achieve robust applications.
Nowadays, camera calibration process consists of adjusting a set of data to a
pin-hole model, assuming that with a reprojection error close to cero, camera
parameters are correct. Since all camera parameters are unknown, computed
results are considered true. However, the pin-hole model does not represent the
camera behavior accurately if the focus is considered. Real cameras change the
focal length slightly to obtain sharp objects in the image and this feature
skews the calibration result if a unique pin-hole model is computed with a
constant focal length. In this paper, a deep analysis of the camera calibration
process is done to detect and strengthen its weaknesses. The camera is mounted
in a robot arm to known extrinsic camera parameters with accuracy and to be
able to compare computed results with the true ones. Based on the bias that
exist between computed results and the true ones, a modification of the widely
accepted camera calibration method using images of a planar template is
presented. A pin-hole model with distance dependent focal length is proposed to
improve the calibration process substantially
