1. A method of confidence estimation for optical flow comprising the steps of: computing a set of features for each pixel of an input image, where the features include image features, matching costs and flow features or flow gradient features; computing smoothed versions of said features; constructing a feature vector for each pixel of the input image; computing a classifier score from said features by employing a set of decision tree classifiers; converting the classifier score into a confidence score.