Pixel matching and motion segmentation in image sequences

Narendra Ahuja, Ram Charan

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper presents a coarse-to-fine algorithm to obtain pixel trajectories in a long image sequence and to segment it into subsets corresponding to distinctly moving objects. Much of the previous related work has addressed the computation of optical flow over two frames or sparse feature trajectories in sequences. The features used are often small in number and restrictive assumptions are made about them such as the visibility of features in all the frames. The algorithm described here uses a coarse scale point feature detector to form a 3-D dot pattern in the spatio temporal space. The trajectories are extracted as 3-D curves-formed by the points using perceptual grouping. Increasingly dense correspondences are obtained iteratively from the sparse feature trajectories. At the finest level, which is the focus of this paper, all pixels are matched and the finest boundaries of the moving objects are obtained.

Original languageEnglish (US)
Title of host publicationRecent Developments in Computer Vision - 2nd Asian Conference on Computer Vision, ACCV 1995, Invited Session Papers
EditorsStan Z. Li, Dinesh P. Mital, Eam Khwang Teoh, Han Wan
PublisherSpringer-Verlag Berlin Heidelberg
Number of pages10
ISBN (Print)9783540607939
StatePublished - 1996
Event2nd Asian Conference on Computer Vision, ACCV 1995 - Singapore, Singapore
Duration: Dec 5 1995Dec 8 1995

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other2nd Asian Conference on Computer Vision, ACCV 1995


  • Feature matching
  • Motion segmentation
  • Optical flow
  • Perceptual grouping
  • Pixel matching
  • Triangulation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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