Classification of Hanging Garments Using Learned Features Extracted from 3D Point Clouds

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F18%3A00323132" target="_blank" >RIV/68407700:21730/18:00323132 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8593741" target="_blank" >https://ieeexplore.ieee.org/document/8593741</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IROS.2018.8593741" target="_blank" >10.1109/IROS.2018.8593741</a>

Result language
angličtina
Original language name
Classification of Hanging Garments Using Learned Features Extracted from 3D Point Clouds
Original language description
The presented work deals with classification of garment categories including pants, shorts, shirts, T-shirts and towels. The knowledge of the garment category is crucial for its robotic manipulation. Our work focuses particularly on garments being held in a hanging state by a robotic arm. The input of our method is a set of depth maps taken from different viewpoints around the garment. The depths are fused into a single 3D point cloud. The cloud is fed into a convolutional neural network that transforms it into a single global feature vector. The network utilizes a generalized convolution operation defined over the local neighborhood of a point. It can deal with permutations of the input points. It was trained on a large dataset of common 3D objects. The extracted feature vector is classified with SVM trained on smaller datasets of garments. The proposed method was evaluated on publicly available data and compared to the original methods, achieving competitive performance and better generalization capability.
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
ISBN
978-1-5386-8095-7
ISSN
2153-0858
e-ISSN
2153-0866
Number of pages
6
Pages from-to
5307-5312
Publisher name
IEEE Press
Place of publication
New York
Event location
Madrid
Event date
Oct 1, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000458872704125

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