Human detection, tracking, and following is one application in which computer vision can be relevant to robotics. By using a sequence of images, a human can be found and that humans movement can be followed. The Microsoft Kinect, one of the most successful color image and depth RGB-D sensors, is known for its human detection capabilities and has multiple software development kits available. The objective of this thesis was to determine if it was feasible to implement human tracking and following on a mobile robot in an indoor environment. Specifically, the tracking was conducted with the Microsoft Kinect and a specific software development environment, Robot Operating System ROS and MATLAB. ROS was utilized to run the drivers for the robot and the Microsoft Kinect, while MATLAB was utilized to run the algorithms and experiments. The skeleton tracking capabilities of the Kinect were utilized as the main tracking system. An auxiliary method was created by using histograms of depth and region properties to segment a person from a depth image. The indoor robot was able to successfully track and follow a person through the indoor environment using the raw sensor data and a combination of the two tracking methods.