Abstract
A novel robust method of estimating optical flow for a dynamic image sequence with poor quality is proposed. In order to estimate the optical flow, in a neighborhood of each interest position, we divide the local region into some sub-regions and then compute the similarity profile for each sub-region by using Orientation Code Matching. These similarity profiles around the position can be used to extract two kinds of voting: positive voting (candidate vectors) and negative voting (suppressing areas). The positive voting can be used to enhance the signal corresponding to the correct optical flows, and the negative voting can be used to reduce noises corresponding to incorrect optical flows. These two votings are integrated into complementary voting in order to extract a reasonable flow together with proper parameters which maximize the signal to noise ratio. The experiments with real image sequences are conducted to show the effectiveness of proposed method.
