Real Time Object Tracking using Reflectional Symmetry and Motion

Many objects found in domestic environments are reflectionally symmetric. In this paper, we present a system that can visually track moving objects by their reflectional symmetry in real time. Apart from the assumption of symmetry, the tracking system does not require any prior object models of the target, such as its colour and shape. The system is robust to shadows and specular reflections. It can also deal with transparent objects. Block motion detection is used in conjunction with symmetry for object tracking. A Kalman filter is used to estimate the object state. Predictions from the Kalman filter is used to improve the efficiency of the symmetry detector. The tracker provides a real time segmentation of an object by searching for motion that is symmetric about the object's mirror line. The tracking system also generates a rotated bounding box, aligned with the object's symmetry line, which can be used as a window for other image processing operations. The final system can track single objects in 640times480 videos at over 40 frames per second using a standard notebook PC