A Video Stabilization Method Based on Improved SIFT

doi:10.3969/j.issn.1006-2475.2024.06.008

Abstract

Abstract:
Abstract： This paper proposes a video stabilization method based on improved SIFT to improve computational efficiency and maintain a good video stabilization effect. Firstly， SIFT is improved and named BO-SIFT （Binarized Octagonal SIFT）. The algorithm introduces concentric octagonal ring feature descriptors， processes the feature vectors by dimensionality reduction and binarization， and then uses Hamming distance for feature point matching， which effectively reduces the description and matching time. Secondly， the BO-SIFT algorithm is applied to video stabilization， extracting the feature points of the video frames for matching and calculating the motion offsets between frames to achieve motion estimation. Afterwards， the estimated motion offsets are smoothed using a Kalman filter and the video frames are inversely compensated using affine transformation to obtain a stabilized image sequence. The experimental results show that the BO-SIFT algorithm reduces the stabilization time by 56.404% compared to the original SIFT algorithm， and the stabilized video of the BO-SIFT algorithm has a higher average peak signal-to-noise ratio compared to the existing better algorithms. In addition， the algorithm in this paper is tested on different videos for video stabilization effects， which also has certain reliability and superiority.

Key words: Key words： video stabilization, BO-SIFT algorithm, dimensionality reduction, binarization, motion estimation, peak signal-to-noise ratio

CLC Number:

TP391.4

LI Xin, JIAO Linan, LIU Youquan, MA Caisha. A Video Stabilization Method Based on Improved SIFT[J]. Computer and Modernization, 2024, 0(06): 43-50.

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