Statistical Shape Representations for Temporal Registration of Plant Components in 3D

Heiwolt, Karoline, Öztireli, Cengiz and Cielniak, Grzegorz (2023) Statistical Shape Representations for Temporal Registration of Plant Components in 3D. In: International Conference on Robotics and Automation 2023, 29 May – 2 June 2023, ExCel, London, UK.

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Statistical shape representations for temporal registration of plant components in 3D
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Item Type:Conference or Workshop contribution (Poster)
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Plants are dynamic organisms and understanding temporal variations in vegetation is an essential problem for robots in the wild. However, associating repeated 3D scans of plants across time is challenging. A key step in this process is re-identifying and tracking the same individual plant components over time. Previously, this has been achieved by comparing their global spatial or topological location. In this work, we demonstrate how using shape features improves temporal organ matching. We present a landmark-free shape compression algorithm, which allows for the extraction of 3D shape features of leaves, characterises leaf shape and curvature efficiently in few parameters, and makes the association of individual leaves in feature space possible. The approach combines 3D contour extraction and further compression using Principal Component Analysis (PCA) to produce a shape space encoding, which is entirely learned from data and retains information about edge contours and 3D curvature. Our evaluation on temporal scan sequences of tomato plants shows, that incorporating shape features improves temporal leaf-matching. A combination of shape, location, and rotation information proves most informative for recognition of leaves over time and yields a true positive rate of 75%, a 15% improvement on sate-of-the-art methods. This is essential for robotic crop monitoring, which enables whole-of-lifecycle phenotyping.

Keywords:3D vision, Agricultural Robotics, Parametric models, spatio-temporal mapping
Subjects:H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G400 Computer Science
D Veterinary Sciences, Agriculture and related subjects > D470 Agricultural Technology
Divisions:COLLEGE OF HEALTH AND SCIENCE > School of Computer Science
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ID Code:55292
Deposited On:16 Aug 2023 12:22

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