Video stabilization for vehicular applications using SURF-like descriptor and KD-tree
This paper describes a method to stabilize video for vehicular applications based on feature analysis. An investigation on camera motion model is conducted. Harris features are extracted under the proposed resolution adaptation scheme. Besides, features are described with SURF-like descriptor. For feature matching, KD-tree with best-bin-first search significantly reduces the matching time. A damping filer is utilized to model and predict the unwanted oscillation. 93.1% correct rate in average is achieved in divergent driving conditions. Only 0.114 second is required to process a frame at resolution 1280×960. The provided benchmark shows outperformance of the proposed method.