A Robust Line Tracking Method based on a Multiple Model Kalman Filter Model for Mobile Projector Systems
Hung Kwun Fung, Kin Hong Wong · Procedia Technology · 2013
Line tracking is essential for many real world applications of computer vision. In thispaper, we propose a computationally efficient line tracker that can robustly andaccurately track lines in an image. We use amultiple-model-Kalman filter (MMKF) scheme which can handle line tracking accurately and robustly. The basic idea is to run N multiple sub-Kalman filters in parallel. Each filter is configuredto use a different state transition model. All the filters are updated by the measurement atthe same time following the conventional Kalman filter update process. The finalprediction is a combination of outputs from all the Kalman filter modules. Theexperimental result shows that the proposed system can track a line robustly in real time. The result is useful in shape detection and should be suitable for building mobile projector applications.