Ali, Haider and Shafait, Faisal and Giannakidou, Eirini and Vakali, Athena and Figueroa, Nadia and Varvadoukas, Theodoros and Mavridis, Nikolaos (2014) Contextual object category recognition for RGB-D scene labeling. Robotics and Autonomous Systems, 62 (2), 241 - 256. Elsevier. doi: 10.1016/j.robot.2013.10.001. ISSN 0921-8890.
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Official URL: http://www.sciencedirect.com/science/article/pii/S0921889013001929
Abstract
Recent advances in computer vision on the one hand, and imaging technologies on the other hand, have opened up a number of interesting possibilities for robust 3D scene labeling. This paper presents contributions in several directions to improve the state-of-the-art in RGB-D scene labeling. First, we present a novel combination of depth and color features to recognize different object categories in isolation. Then, we use a context model that exploits detection results of other objects in the scene to jointly optimize labels of co-occurring objects in the scene. Finally, we investigate the use of social media mining to develop the context model, and provide an investigation of its convergence. We perform thorough experimentation on both the publicly available RGB-D Dataset from the University of Washington as well as on the {NYU} scene dataset. An analysis of the results shows interesting insights about contextual object category recognition, and its benefits.
Item URL in elib: | https://elib.dlr.de/97147/ | ||||||||||||||||||||||||||||||||
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Document Type: | Article | ||||||||||||||||||||||||||||||||
Title: | Contextual object category recognition for RGB-D scene labeling | ||||||||||||||||||||||||||||||||
Authors: |
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Date: | 1 February 2014 | ||||||||||||||||||||||||||||||||
Journal or Publication Title: | Robotics and Autonomous Systems | ||||||||||||||||||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||||||||||||||||||
Open Access: | No | ||||||||||||||||||||||||||||||||
Gold Open Access: | No | ||||||||||||||||||||||||||||||||
In SCOPUS: | Yes | ||||||||||||||||||||||||||||||||
In ISI Web of Science: | Yes | ||||||||||||||||||||||||||||||||
Volume: | 62 | ||||||||||||||||||||||||||||||||
DOI: | 10.1016/j.robot.2013.10.001 | ||||||||||||||||||||||||||||||||
Page Range: | 241 - 256 | ||||||||||||||||||||||||||||||||
Publisher: | Elsevier | ||||||||||||||||||||||||||||||||
ISSN: | 0921-8890 | ||||||||||||||||||||||||||||||||
Status: | Published | ||||||||||||||||||||||||||||||||
Keywords: | Object recognition; Contextual modeling; RGB-D scenes; Social media; 3D scene labeling | ||||||||||||||||||||||||||||||||
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) | ||||||||||||||||||||||||||||||||
Deposited By: | Ali, Haider | ||||||||||||||||||||||||||||||||
Deposited On: | 09 Jul 2015 10:25 | ||||||||||||||||||||||||||||||||
Last Modified: | 06 Nov 2023 14:36 |
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