3D Motion Completion in Crowded Scenes

Niv Gafni, Andrei Sharf

Research output: Contribution to journalArticlepeer-review


Crowded motions refer to multiple objects moving around and interacting such as crowds, pedestrians and etc. We capture crowded scenes using a depth scanner at video frame rates. Thus, our input is a set of depth frames which sample the scene over time. Processing such data is challenging as it is highly unorganized, with large spatiotemporal holes due to many occlusions. As no correspondence is given, locally tracking 3D points across frames is hard due to noise and missing regions. Furthermore global segmentation and motion completion in presence of large occlusions is ambiguous and hard to predict. Our algorithm utilizes Gestalt principles of common fate and good continuity to compute motion tracking and completion respectively. Our technique does not assume any pregiven markers or motion template priors. Our key-idea is to reduce the motion completion problem to a 1D curve fitting and matching problem which can be solved efficiently using a global optimization scheme. We demonstrate our segmentation and completion method on a variety of synthetic and real world crowded scanned scenes.

Original languageEnglish
Pages (from-to)65-74
Number of pages10
JournalComputer Graphics Forum
Issue number5
StatePublished - Aug 2014


  • Categories and Subject Descriptors (according to ACM CCS)
  • I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism -

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design


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