A Model-Based Approach to Recovering the Structure of a Plant from Images
van den Hengel, Anton
Tester, Mark A.
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
Desert Agriculture Initiative
Plant Science Program
Preprint Posting Date2015-03-11
Online Publication Date2015-03-19
Print Publication Date2015
Permanent link to this recordhttp://hdl.handle.net/10754/556196
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AbstractWe 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.
Conference/Event name13th European Conference on Computer Vision, ECCV 2014