A fast near-duplicate keyframe detection method based on local features

Fast near-duplicate keyframe detection is the basis of similar video content and video topic analysis. Traditional solutions based on local features are time-consuming and unsuitable for real-time applications. Considering there are little changes on the angles between similar video keyframes, a fast near-duplicate keyframe detection method based on local features is proposed. Firstly, the feature points are detected in various scales of image pyramids by adopting FAST (Features from Accelerated Segment Test) detection method. Secondly, each feature point is described by BRIEF algorithm. Thirdly, the similar keyframes are recognized based on the pattern entropy. Experiments prove that the proposed method is accurate and efficient, and is suitable for real-time applications of similar video keyframes detection.