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.