Object movements synopsis via part assembling and stitching

Yongwei Nie, Hanqiu Sun, Ping Li, Chunxia Xiao, Kwan Liu Ma

Research output: Journal article publicationJournal articleAcademic researchpeer-review

31 Citations (Scopus)


Video synopsis aims at removing video's less important information, while preserving its key content for fast browsing, retrieving, or efficient storing. Previous video synopsis methods, including frame-based and object-based approaches that remove valueless whole frames or combine objects from time shots, cannot handle videos with redundancies existing in the movements of video object. In this paper, we present a novel part-based object movements synopsis method, which can effectively compress the redundant information of a moving video object and represent the synopsized object seamlessly. Our method works by part-based assembling and stitching. The object movement sequence is first divided into several part movement sequences. Then, we optimally assemble moving parts from different part sequences together to produce an initial synopsis result. The optimal assembling is formulated as a part movement assignment problem on a Markov Random Field (MRF), which guarantees the most important moving parts are selected while preserving both the spatial compatibility between assembled parts and the chronological order of parts. Finally, we present a non-linear spatiotemporal optimization formulation to stitch the assembled parts seamlessly, and achieve the final compact video object synopsis. The experiments on a variety of input video objects have demonstrated the effectiveness of the presented synopsis method.

Original languageEnglish
Article number6702519
Pages (from-to)1303-1315
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number9
Publication statusPublished - Sept 2014
Externally publishedYes


  • belief propagation
  • MRF optimization
  • part assembling
  • part stitching
  • Video synopsis

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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