elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Persistent Anytime Learning of Objects from Unseen Classes

Denninger, Maximilian and Triebel, Rudolph (2018) Persistent Anytime Learning of Objects from Unseen Classes. In: IEEE International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018), 01 Oct - 05 Oct 2018, Madrid, Spain.

[img] PDF
982kB

Abstract

We present a fast and very effective method for object classification that is particularly suited for robotic applications such as grasping and semantic mapping. Our approach is based on a Random Forest classifier that can be trained incrementally. This has the major benefit that semantic information from new data samples can be incorporated without retraining the entire model. Even if new samples from a previously unseen class are presented, our method is able to perform efficient updates and learn a sustainable representation for this new class. Further features of our method include a very fast and memory-efficient implementation, as well as the ability to interrupt the learning process at any time without a significant performance degradation. Experiments on benchmark data for robotic applications show the clear benefits of our incremental approach and its competitiveness with standard offline methods in terms of classification accuracy.

Item URL in elib:https://elib.dlr.de/123987/
Document Type:Conference or Workshop Item (Other)
Title:Persistent Anytime Learning of Objects from Unseen Classes
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Denninger, Maximilianmaximilian.denninger (at) dlr.dehttps://orcid.org/0000-0002-1557-2234
Triebel, RudolphRudolph.Triebel (at) dlr.deUNSPECIFIED
Date:1 October 2018
Journal or Publication Title:IEEE International Conference on Intelligent Robots and Systems
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Status:Published
Keywords:Learning and Adaptive Systems, Object Detection, Segmentation and Categorization, Online Learning, Random Forest
Event Title:IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018)
Event Location:Madrid, Spain
Event Type:international Conference
Event Dates:01 Oct - 05 Oct 2018
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben Multisensorielle Weltmodellierung
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Perception and Cognition
Deposited By: Denninger, Maximilian
Deposited On:30 Nov 2018 14:39
Last Modified:31 Jul 2019 20:21

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.