ReVeS Participation - Tree Species Classification using Random Forests and Botanical Features

Abstract : This paper summarizes the participation of the ReVeS project to the ImageCLEF 2012 Plant Identification task. Aiming to develop a system for tree leaf identification on mobile devices, our method is designed to cope with the challenges of complex natural images and to enable a didactic interaction with the user. The approach relies on a two step model-driven segmentation and on the evaluation of high-level characteristics that make a semantic interpretation possible, as well as more generic shape features. All these descriptors are combined in a random forest classification algorithm, and their significance evaluated. Our team ranks 4th overall, 3rd on natural images, which constitutes a very satisfying performance with respect to the project's objectives.
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https://hal.archives-ouvertes.fr/hal-00759848
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Submitted on : Monday, December 3, 2012 - 9:23:12 AM
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Guillaume Cerutti, Violaine Antoine, Laure Tougne, Julien Mille, Lionel Valet, et al.. ReVeS Participation - Tree Species Classification using Random Forests and Botanical Features. Conference and Labs of the Evaluation Forum (CLEF), Sep 2012, Rome, Italy. pp.1. ⟨hal-00759848⟩

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