Improved global motion estimation via motion vector clustering for video stabilization

Bo Hao Chen, Andrey Kopylov, Shih Chia Huang, Oleg Seredin, Roman Karpov, Sy Yen Kuo, K. Robert Lai, Tan Hsu Tan, Munkhjargal Gochoo, Damdinsuren Bayanduuren, Cihun Siyong Gong, Patrick C.K. Hung

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


Video stabilization technique is often used in handheld multimedia devices, whereas the difficulties in the accurate extraction aspect of global motion vectors restrict its development. This paper proposes a novel video stabilization approach that is based on the shortest spanning path clustering algorithm for effective and reliable estimation of the global motion vectors. As demonstrated in our experimental results, the proposed approach achieves superior stabilized effectiveness compared with the other state-of-the-art approaches based on both qualitative and quantitative measurements.

Original languageEnglish
Pages (from-to)39-48
Number of pages10
JournalEngineering Applications of Artificial Intelligence
Publication statusPublished - Sept 1 2016
Externally publishedYes


  • Motion vector clustering
  • Shortest spanning path
  • Video stabilization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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