Background extraction using random walk image fusion

Kai Lung Hua, Hong Cyuan Wang, Chih Hsiang Yeh, Wen-Huang Cheng, Yu Chi Lai

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


It is important to extract a clear background for computer vision and augmented reality. Generally, background extraction assumes the existence of a clean background shot through the input sequence, but realistically, situations may violate this assumption such as highway traffic videos. Therefore, our probabilistic model-based method formulates fusion of candidate background patches of the input sequence as a random walk problem and seeks a globally optimal solution based on their temporal and spatial relationship. Furthermore, we also design two quality measures to consider spatial and temporal coherence and contrast distinctness among pixels as background selection basis. A static background should have high temporal coherence among frames, and thus, we improve our fusion precision with a temporal contrast filter and an optical-flow-based motionless patch extractor. Experiments demonstrate that our algorithm can successfully extract artifact-free background images with low computational cost while comparing to state-of-the-art algorithms.

Original languageEnglish
Pages (from-to)423-435
Number of pages13
JournalIEEE Transactions on Cybernetics
Issue number1
StatePublished - 1 Jan 2018


  • Background estimation
  • Background extraction
  • Background initialization
  • Image fusion
  • Random walk (RW)


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