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Type: Conference paper
Title: A model-based approach to recovering the structure of a plant from images
Author: Ward, B.
Bastian, J.
van den Hengel, A.
Pooley, D.
Rajendra, B.
Berger, B.
Tester, M.
Citation: Proceedings of the 13th European Conference on Computer Vision Workshops (ECCV 2014), as published in Lecture Notes in Computer Science, 2015 / Agapito, L., Bronstein, M., Rother, C. (ed./s), vol.8928, pp.215-230
Publisher: Springer International Publishing
Publisher Place: Switzerland
Issue Date: 2015
Series/Report no.: Lecture Notes in Computer Science; 8928
ISBN: 9783319162195
ISSN: 0302-9743
Conference Name: 13th European Conference on Computer Vision Workshops (ECCV 2014) (06 Sep 2014 - 07 Sep 2014 : Zurich, Switzerland)
Statement of
Ben Ward, John Bastian, Anton van den Hengel, Daniel Pooley, Rajendra Bari, Bettina Berger, and Mark Tester
Abstract: We present a method for recovering the structure of a plant directly from a small set of widely-spaced images for automated analysis of phenotype. Structure recovery is more complex than shape estimation, but the resulting structure estimate is more closely related to phenotype than is a 3D geometric model. The method we propose is applicable to a wide variety of plants, but is demonstrated on wheat. Wheat is composed of thin elements with few identifiable features, making it difficult to analyse using standard feature matching techniques. Our method instead analyses the structure of plants using only their silhouettes. We employ a generate-and-test method, using a database of manually modelled leaves and a model for their composition to synthesise plausible plant structures which are evaluated against the images. The method is capable of efficiently recovering accurate estimates of plant structure in a wide variety of imaging scenarios, without manual intervention.
Keywords: Plant phenotyping; image processing; plant architecture
Description: ECCV 2014 Workshops, Part IV, LNCS 8928
Rights: © Springer International Publishing Switzerland 2015
RMID: 0030026273
DOI: 10.1007/978-3-319-16220-1_16
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Appears in Collections:Computer Science publications

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