A Real-Time Compressive Tracking System for Amphibious Spherical Robots

Given the special working environments and application functions of the amphibious robot, an improved RGB-D visual tracking algorithm with dual trackers is proposed and implemented in this chapter. Compressive tracking (CT) was selected as the basis of the proposed algorithm to process colour images from a RGB-D camera, and a Kalman filter with a second-order motion model was added to the CT tracker to predict the state of the target, select candidate patches or samples, and reinforce the tracker's robustness to high-speed moving targets. In addition, a variance ratio features shift (VR-V) tracker with a Kalman prediction mechanism was adopted to process depth images from a RGB-D camera. A visible and infrared fusion mechanism or feedback strategy is introduced in the proposed algorithm to enhance its adaptability and robustness. To evaluate the effectiveness of the algorithm, Microsoft Kinect, which is a combination of colour and depth cameras, was adopted for use in a prototype of the robotic tracking system.