Feature guided pixel matching and segmentation in motion image sequences

Ram Charan, Narendra Ahuja

Research output: Contribution to conferencePaper

Abstract

The problem of feature correspondences and trajectory finding for a long image sequence has received considerable attention. Most attempts involve small numbers of features and make restrictive assumptions such as the visibility of features in all the frames. In this paper, a coarse-to-fine algorithm is described to obtain pixel trajectories through the sequence and to segment into subsets corresponding to distinctly moving objects. The algorithm 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, matching of all pixels is done using intensity correlation and the finest boundaries of the moving objects are obtained.

Original languageEnglish (US)
Pages277-282
Number of pages6
StatePublished - Dec 1 1995
EventInternational Symposium on Computer Vision, ISCV'95, Proceedings - Coral Gables, FL, USA
Duration: Nov 21 1995Nov 23 1995

Other

OtherInternational Symposium on Computer Vision, ISCV'95, Proceedings
CityCoral Gables, FL, USA
Period11/21/9511/23/95

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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    Charan, R., & Ahuja, N. (1995). Feature guided pixel matching and segmentation in motion image sequences. 277-282. Paper presented at International Symposium on Computer Vision, ISCV'95, Proceedings, Coral Gables, FL, USA, .