Automatic video mosaicking algorithm via dynamic key-frame

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number9082306
Pages (from-to)272-278
Number of pages7
JournalJournal of Systems Engineering and Electronics
Volume31
Issue number2
DOIs
Publication statusPublished - Apr 2020
Externally publishedYes

Keywords

  • image stitching
  • mapping
  • panorama
  • speeded up robust feature (SURF)
  • video mosaicking

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