An efficient method for camera calibration from 2D images is important in many computer vision tasks such as stereo vision, metrology, and 3D reconstruction. There are many of tasks that can benefit from camera parameter information, such as distance estimation, detecting and classifying of objects in addition to 3D view generation. Camera parameters are important for vision-based robot to move from one location to another. Without camera parameters it is difficult to find and evaluate the properties of the object. Camera parameters are important for the extraction of 3D spatial information of the object from a 2D image. Camera calibration is also critical for estimating information about 3D depth. Another prerequisite for camera calibration is the creation of a 3D view from a 2D view. Reconstruction of a 3D view of an indoor corridor is the main objective of this work. In order to achieve 3D reconstruction from a 2D camera, the parameters have to be taken into consideration. By using the camera parameters, distance estimation has performed for robot navigation. Using traditional calibration methods can become impractical because of a lack of objects for reference or even fixed patterns in the indoor environment.

Calibration, distance, vanishing point, edges, skirting.