Automatic video mosaicking algorithm via dynamic key-frame

Yufeng Ji, Weixing Li*, Kai Feng, Boyang Xing, Feng Pan

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

5 引用 (Scopus)

摘要

Automatic video mosaicking is a challenging task in computer vision. Current researches consider either panoramic or mapping tasks on short videos. In this paper, an automatic mosaicking algorithm is proposed for both mapping and panoramic tasks based on the adapted key-frame on videos of any length. The speeded up robust features (SURF) and the grid motion statistic (GMS) algorithm are used for feature extraction and matching between consecutive frames, which are used to compute the transformation. In order to reduce the influence of the accumulated error during image stitching, an evaluation metric is put forward for the transformation matrix. Besides, a self-growth method is employed to stitch the global image for long videos. The algorithm is evaluated by using aerial-view and panoramic videos respectively on the graphic processing unit (GPU) device, which can satisfy the real-Time requirement. The experimental results demonstrate that the proposed algorithm is able to achieve a better performance than the state-of-Art.

源语言英语
文章编号9082306
页(从-至)272-278
页数7
期刊Journal of Systems Engineering and Electronics
31
2
DOI
出版状态已出版 - 4月 2020
已对外发布

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引用此

Ji, Y., Li, W., Feng, K., Xing, B., & Pan, F. (2020). Automatic video mosaicking algorithm via dynamic key-frame. Journal of Systems Engineering and Electronics, 31(2), 272-278. 文章 9082306. https://doi.org/10.23919/JSEE.2020.000005