Calibration of depth cameras using feature points matching technique

Geometric camera calibration has been a well-studied area in computer vision. However, with the emergence of imaging systems composing both color cameras and infrared (IR) cameras, there is a need to develop a more e fficient calibration algorithm to take advantage of the depth information provided by IR cameras. In this thesis, we propose a new camera calibration algorithm that utilizes the depth data. It matches feature points in the master camera frame with feature points in the slave camera frame, and then it estimates the extrinsic parameters through a two-stage error minimization process. Experiments were conducted to test the performance of the algorithm using different feature detectors and methods to eliminate false matching points.U of I OnlyUndergraduate senior thesis not recommended for open acces