RGB-D Segmentation of Poultry Entrails

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4 Citationer (Scopus)
358 Downloads (Pure)

Abstrakt

This paper presents an approach for automatic visual inspection of chicken entrails in RGB-D data. The point cloud is first over-segmented into supervoxels based on color, spatial and geometric information. Color, position and texture features are extracted from each of the resulting supervoxels and passed to a Random Forest classifier, which classifies the supervoxels as either belonging to heart, lung, liver or misc. The dataset consists of 150 individual entrails, with 30 of these being reserved for evaluation. Segmentation performance is evaluated on a voxel-by-voxel basis, achieving an average Jaccard index of 61.5% across the four classes of organs. This is a 5.9% increase over the 58.1% achieved with features derived purely from 2D.
OriginalsprogEngelsk
TitelIX International Conference on Articulated Motion and Deformable Objects
ForlagSpringer
Publikationsdato2016
Sider168-174
ISBN (Trykt)978-3-319-41778-3
DOI
StatusUdgivet - 2016
BegivenhedIX Conference on Articulated Motion and Deformable Objects - Mallorca, Spanien
Varighed: 13 jul. 201615 jul. 2016
http://amdo2016.uib.es/

Konference

KonferenceIX Conference on Articulated Motion and Deformable Objects
LandSpanien
ByMallorca
Periode13/07/201615/07/2016
Internetadresse
NavnLecture Notes in Computer Science
Vol/bind9756
ISSN0302-9743

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