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Non-Rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding

Chiotellis, Ioannis and Triebel, Rudolph and Windheuser, Thomas and Cremers, Daniel (2016) Non-Rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding. In: ECCV. European Conference on Computer Vision (ECCV), Amsterdam, Netherlands.

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In this paper, we propose a highly efficient metric learning approach to non-rigid 3D shape analysis. From a training set of 3D shapes from different classes, we learn a transformation of the shapes which optimally enforces a clustering of shapes from the same class. In contrast to existing approaches, we do not perform a transformation of individual local point descriptors, but a linear embedding of the entire distribution of shape descriptors. It turns out that this embedding of the input shapes is sufficiently powerful to enable state of the art retrieval performance using a simple nearest neighbor classifier. We demonstrate experimentally that our approach substantially outperforms the state of the art non-rigid 3D shape retrieval methods on the recent benchmark data set SHREC’14 Non-Rigid 3D Human Models, both in classification accuracy and runtime.

Item URL in elib:https://elib.dlr.de/109446/
Document Type:Conference or Workshop Item (Poster)
Additional Information:<a href="https://github.com/tum-vision/csdlmnn" target="blank">code</a>
Title:Non-Rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Chiotellis, IoannisTUMUNSPECIFIED
Windheuser, ThomasTUMUNSPECIFIED
Cremers, DanieltumUNSPECIFIED
Journal or Publication Title:ECCV
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:shape retrieval, shape representation, supervised learning
Event Title:European Conference on Computer Vision (ECCV)
Event Location:Amsterdam, Netherlands
Event Type:international Conference
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Vorhaben Multisensorielle Weltmodellierung (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Perception and Cognition
Deposited By: Triebel, Rudolph
Deposited On:20 Dec 2016 11:04
Last Modified:31 Jul 2019 20:06

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