Dynamic estimation of optical flow field using objective functions

Zhao Wei-Zhao, Qi Fei-Hu, Young Tzay Y

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Optical flow (image velocity) fields are computed and interpreted from an image sequence by incorporating knowledge of object kinematics. Linear and quadratic objective functions are defined by considering the kinematics, and the function parameters are estimated simultaneously with the computation of the velocity field by relaxation. The objective functions provide an interpretation of the dynamic scenes and, at the same time, serve as the smoothness constraints. The computation is initially based on measured perpendicular velocity components of contours or region boundaries which, due to the 'aperture problem', are theoretically not the true perpendicular velocity components. This difficulty is alleviated by introducing a dynamic procedure for the measurement of the perpendicular components. Experiments on using objective functions for synthetic and real images of translating and rotating objects generated velocity fields that are meaningful and consistent with visual perception.

Original languageEnglish (US)
Pages (from-to)259-267
Number of pages9
JournalImage and Vision Computing
Issue number4
StatePublished - Nov 1989


  • dynamic estimation
  • image velocity field
  • motion analysis
  • objective function
  • optical flow
  • relaxation algorithm

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering


Dive into the research topics of 'Dynamic estimation of optical flow field using objective functions'. Together they form a unique fingerprint.

Cite this