Research on global motion estimation based on adaptive SIFT algorithm
Huiqing Zhang, Jiancheng An, Luguang Cao · 2012
Based on time redundancy in video image sequences an adaptive SIFT (Scale-invariant feature transform) algorithm is proposed. According to the latest three models' outputs in global motion estimation, the algorithm predicts overlapping regions between reference and current frames by using Lagrange parabolic interpolation, and then extracts feature points in the smaller region instead of the whole image. In this way, it can eliminate a large number of information redundancies to increase the processing speed of each frame, improve the effectiveness of feature points and reduce the mismatch. Experimental results show that the improved algorithm has the features of strong adaptive ability, rapidity and high matching accuracy, and it can be applied to the real-time positioning.