Mean-Shift based Object Tracking Algorithm using SURF Features

摘要

Mean-Shift tracking is primarily used for carrying out localized search on an image frame using colour histograms. The application of mean-shift tracking directly to SURF features is limited due to the unavailability of sufficient number of key points for a given object. This paper proposes a method called re-projection to overcome this limitation so that the mean-shift algorithm can be used directly with SURF descriptors for tracking an object in a video recorded from a non-stationary camera. Since the SURF features are computed only for the object being tracked, the computational requirement is small enough to allow real-time tracking of the object. The efficacy of the approach is demonstrated through various simulation results.