Nuricumbo, Jorge René und Ali, Haider und Marton, Zoltan Csaba und Grzegorzek, Marcin (2015) Improving object classification robustness in RGB-D using adaptive SVMs. Multimedia Tools and Applications : An International Journal, Seiten 1-19. Springer. doi: 10.1007/s11042-015-2612-7. ISSN 1380-7501.
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Offizielle URL: http://dx.doi.org/10.1007/s11042-015-2612-7
Kurzfassung
Nowadays object recognition is a fundamental capability for an autonomous robot in interaction with the physical world. Taking advantage of new sensing technologies providing RGB-D data, the object recognition capabilities increase dramatically. Object recognition has been well studied, however, known object classifiers usually feature poor generality and, therefore, limited adaptivity to different application domains. Although some domain adaptation approaches have been presented for RGB data, little work has been done on understanding the effects of applying object classification algorithms using RGB-D for different domains. Addressing this problem, we propose and comprehensively investigate an approach for object recognition in RGB-D data that uses adaptive Support Vector Machines (aSVM) and, in this way, achieves an impressive robustness in cross-domain adaptivity. For evaluation, two datasets from different application domains were used. Moreover, a study of state-of-the-art RGB-D feature extraction techniques and object classification methods was performed to identify which combinations (object representation - classification algorithm) remain less affected in terms of performance while switching between different application domains.
elib-URL des Eintrags: | https://elib.dlr.de/97149/ | ||||||||||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||||||
Titel: | Improving object classification robustness in RGB-D using adaptive SVMs | ||||||||||||||||||||
Autoren: |
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Datum: | 16 Mai 2015 | ||||||||||||||||||||
Erschienen in: | Multimedia Tools and Applications : An International Journal | ||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||
Open Access: | Nein | ||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||
DOI: | 10.1007/s11042-015-2612-7 | ||||||||||||||||||||
Seitenbereich: | Seiten 1-19 | ||||||||||||||||||||
Verlag: | Springer | ||||||||||||||||||||
ISSN: | 1380-7501 | ||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||
Stichwörter: | Adaptive SVM; aSVM; RGB-D; Kinect | ||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||
HGF - Programmthema: | Technik für Raumfahrtsysteme | ||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||
DLR - Forschungsgebiet: | R SY - Technik für Raumfahrtsysteme | ||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Vorhaben Multisensorielle Weltmodellierung (alt) | ||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||
Institute & Einrichtungen: | Institut für Robotik und Mechatronik (ab 2013) | ||||||||||||||||||||
Hinterlegt von: | Ali, Haider | ||||||||||||||||||||
Hinterlegt am: | 09 Jul 2015 10:28 | ||||||||||||||||||||
Letzte Änderung: | 08 Mär 2018 18:37 |
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