Abstract:

Accurate tracking results are unobtainable by the traditional algorithm of Mean Shift due to noise,rotation and changed scales of the target etc.A shape context tracking algorithm for Mean Shift objects is proposed by combining the current popular target tracking algorithm and local features.The contour information and features of shape context are extracted from the target.Then a shape context histogram is established according to the locations and spacing of sample points and the histograms of all the points constitutes the shape context feature of the image  after which the Mean Shift algorithm is adopted for tracking.The experimental results show that the algorithm can accurately track the object with scale change,rotation,noise and is of good accuracy and robustness.

Key words: local feature;shape context;mean shift;target tracking