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@ARTICLE{Dellen:139562,
      author       = {Dellen, B. and Scharr, Hanno and Torras, C.},
      title        = {{G}rowth signature of rosette plants from time-lapse video},
      journal      = {IEEE ACM transactions on computational biology and
                      bioinformatics},
      volume       = {PP},
      number       = {99},
      issn         = {1557-9964},
      address      = {New York, NY},
      publisher    = {IEEE},
      reportid     = {FZJ-2013-05546},
      pages        = {1-11},
      year         = {2015},
      abstract     = {Plant growth is a dynamic process, and the precisecourse of
                      events during early plant development is of majorinterest
                      for plant research. In this work, we investigate thegrowth
                      of rosette plants by processing time-lapse videos ofgrowing
                      plants, where we use Nicotiana tabacum (tobacco) asa model
                      plant. In each frame of the video sequences, potentialleaves
                      are detected using a leaf-shape model. These detectionsare
                      prone to errors due to the complex shape of plants andtheir
                      changing appearance in the image, depending on leafmovement,
                      leaf growth, and illumination conditions. To copewith this
                      problem, we employ a novel graph-based trackingalgorithm
                      which can bridge gaps in the sequence by linkingleaf
                      detections across a range of neighboring frames. We use
                      theoverlap of fitted leaf models as a pairwise similarity
                      measure, andforbid graph edges that would link leaf
                      detections within a singleframe. We tested the method on a
                      set of tobacco-plant growthsequences, and could track the
                      first leaves of the plant, includingpartially or temporarily
                      occluded ones, along complete sequences,demonstrating the
                      applicability of the method to automatic plantgrowth
                      analysis. All seedlings displayed approximately the
                      samegrowth behavior, and a characteristic growth signature
                      wasfound.},
      cin          = {IBG-2},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {582 - Plant Science (POF3-582)},
      pid          = {G:(DE-HGF)POF3-582},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000368292400027},
      doi          = {10.1109/TCBB.2015.2404810},
      url          = {https://juser.fz-juelich.de/record/139562},
}