Literature DB >> 19424454

MOTION FLOW ESTIMATION FROM IMAGE SEQUENCES WITH APPLICATIONS TO BIOLOGICAL GROWTH AND MOTILITY.

Gang Dong1, Tobias I Baskin, Kannappan Palaniappan.   

Abstract

In this paper, a new method for motion flow estimation that considers errors in all the derivative measurements is presented. Based on the total least squares (TLS) model, we accurately estimate the motion flow in the general noise case by combining noise model (in form of covariance matrix) with a parametric motion model. The proposed algorithm is tested on two different types of biological motion, a growing plant root and a gastrulating embryo, with sequences obtained microscopically. The local, instantaneous velocity field estimated by the algorithm reveals the behavior of the underlying cellular elements.

Year:  2006        PMID: 19424454      PMCID: PMC2678006          DOI: 10.1109/ICIP.2006.312551

Source DB:  PubMed          Journal:  Proc Int Conf Image Proc        ISSN: 1522-4880


  3 in total

Review 1.  How we are shaped: the biomechanics of gastrulation.

Authors:  Ray Keller; Lance A Davidson; David R Shook
Journal:  Differentiation       Date:  2003-04       Impact factor: 3.880

2.  Accurate dense optical flow estimation using adaptive structure tensors and a parametric model.

Authors:  Haiying Liu; Rama Chellappa; Azriel Rosenfeld
Journal:  IEEE Trans Image Process       Date:  2003       Impact factor: 10.856

3.  Analysis of cell division and elongation underlying the developmental acceleration of root growth in Arabidopsis thaliana.

Authors:  G T Beemster; T I Baskin
Journal:  Plant Physiol       Date:  1998-04       Impact factor: 8.340

  3 in total
  1 in total

1.  Fast Graph Partitioning Active Contours for Image Segmentation Using Histograms.

Authors:  Sumit K Nath; Kannappan Palaniappan
Journal:  EURASIP J Image Video Process       Date:  2010-01-26
  1 in total

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