Vision allows one to react to rapid changes in the surrounding environment. The ability of animals to control their eye movements and follow a moving target has always been a focus in biological research. The biological control system that governs the eye movements is known as the oculomotor control system. Generally, the control of eye movements to follow a moving visual target is known as gaze control.
The primary goal of motion tracking is to keep an object of interest, generally known as the visual target, in the view of the observer at all time. Tracking can be driven by changes perceived from the real world. One obvious change introduced by a moving object is the change in its location, which can be described in terms of displacement. In this project, we will show that by using stereo disparity and optical flow, two significant types of displacements, as the major source of directing signals in a robotic gaze control system, we can determine where the moving object is located and perform the tracking duty, without recognizing what the object is.
The recent advances in computer hardware, exemplified by our Datacube MaxVideo 200 system and a network of Transputers, make it possible to perform image processing operations at video rates, and to implement real-time systems with input images obtained from video cameras. The main purposes of this project are to establish some simple control theories to monitor changes perceived in the real world, and to apply such theories in the implementation of a real-time three-dimensional motion tracking system on a binocular camera head system installed in the Laboratory for Computational Intelligence (LCI) at the Department of Computer Science of the University of British Columbia (UBC).
The control scheme of our motion tracking system is based on the Perception-Reasoning-Action (PRA) regime. We will describe an approach of using an active monitoring process together with a process for accumulating temporal data to allow different hardware components running at different rates to communicate and cooperate in a real-time system working on real world data. We will also describe a cancellation method to reduce the unstable effects of background optical flow generated from ego-motion, and create a ``pop-out'' effect in the motion field to ease the burden of target selection. The results of various experiments conducted, and the difficulties of tracking without any knowledge of the world and the objects will also be discussed.
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