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|Title:||A model-based approach to recovering the structure of a plant from images|
van den Hengel, A.
|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|
|Series/Report no.:||Lecture Notes in Computer Science; 8928|
|Conference Name:||13th European Conference on Computer Vision Workshops (ECCV 2014) (06 Sep 2014 - 07 Sep 2014 : Zurich, Switzerland)|
|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|
|Appears in Collections:||Computer Science publications|
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