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Authors: Supawadee Chaivivatrakul ; Jednipat Moonrinta and Matthew N. Dailey

Affiliation: Asian Institute of Technology, Thailand

ISBN: 978-989-674-028-3

Keyword(s): Object detection, Keypoint detection, Keypoint descriptors, Keypoint classification, Image segmentation, Structure from motion, 3D reconstruction, Ellipsoid estimation, Pineapple, Mobile field robot, Agricultural automation.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image Formation and Preprocessing ; Implementation of Image and Video Processing Systems

Abstract: Towards automation of crop yield estimation for pineapple fields, we present a method for detection and 3D reconstruction of pineapples from a video sequence acquired, for example, by a mobile field robot. The detection process incorporates the Harris corner detector, the SIFT keypoint descriptor, and keypoint classification using a SVM. The 3D reconstruction process incorporates structure from motion to obtain a 3D point cloud representing patches of the fruit's surface followed by least squares estimation of the quadric (in this case an ellipsoid) best fitting the 3D point cloud. We performed three experiments to establish the feasibility of the method. Experiments 1 and 2 tested the performance of the Harris, SIFT, and SVM method on indoor and outdoor data. The method achieved a keypoint classification accuracy of 87.79% on indoor data and 76.81% on outdoor data, against base rates of 81.42% and 53.83%, respectively. In Experiment 3, we performed 3D reconstruction from indoor d ata. The method achieved an average of 34.96% error estimating the ratio of the fruits' major axis to short axis length. Future work will focus on increasing the robustness and accuracy of the 3D reconstruction method as well as resolving the 3D scale ambiguity. (More)

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Paper citation in several formats:
Chaivivatrakul S.; Moonrinta J.; N. Dailey M. and (2010). TOWARDS AUTOMATED CROP YIELD ESTIMATION - Detection and 3D Reconstruction of Pineapples in Video Sequences.In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-028-3, pages 180-183. DOI: 10.5220/0002838201800183

@conference{visapp10,
author={Supawadee Chaivivatrakul and Jednipat Moonrinta and Matthew {N. Dailey}},
title={TOWARDS AUTOMATED CROP YIELD ESTIMATION - Detection and 3D Reconstruction of Pineapples in Video Sequences},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={180-183},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002838201800183},
isbn={978-989-674-028-3},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)
TI - TOWARDS AUTOMATED CROP YIELD ESTIMATION - Detection and 3D Reconstruction of Pineapples in Video Sequences
SN - 978-989-674-028-3
AU - Chaivivatrakul, S.
AU - Moonrinta, J.
AU - N. Dailey, M.
PY - 2010
SP - 180
EP - 183
DO - 10.5220/0002838201800183

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