A Robust Visual Tracking Method for Unmanned Mobile Systems

Abstract

This paper introduces a robust visual tracking of objects in complex environments with blocking obstacles and light reflection noises. This visual tracking method utilizes a transfer matrix to project image pixels back to real-world coordinates. During the image process, a color and shape test is used to recognize the object and a vector is used to represent the object, which contains the information of orientation and body length of the object. If the object is partially blocked by the obstacles or the reflection from the water surface, the vector predicts the position of the object. During the real-time tracking, a Kalman filter is used to optimize the result. To validate the method, the visual tracking algorithm was tested by tracking a submarine and a fish on the water surface of a water tank, above which three pieces of blur glass were blocking obstacles between the camera and the object. By using this method, the interference from the reflection of the side glass and the fluctuation of the water surface can be also avoided.