Category level 3D object recognition using depth images

Author

Kayim, G. ; Akgul, C.B. ; Sankur, B.

Author_Institution

Elektrik ve Elektron. Muhendisligi Bolumu, Bogazici Univ., İstanbul, Turkey

fYear

2013

fDate

24-26 April 2013

Firstpage

1

Lastpage

4

Abstract

In this study the focus was on the one of the latest trending topics, 3D object recognition, which became trending by the developments in the 3d imaging technologies. One of the methods that is used was developed directly for 3D object recognition and the other one was developed for 2D leaf recognition. The second one was adapted for 3D object recognition. Both methods are global methods. Their separate and fused performances were examined. On full object models both methods performs well, and due to their structure they are promising methods for partial object models.

Keywords

object recognition; solid modelling; 2D leaf recognition; 3D imaging technology; category level 3D object recognition; depth images; global methods; partial object models; Adaptation models; Histograms; Object recognition; Robots; Shape; Solid modeling; Three-dimensional displays; 3D object recognition; feature fusion; full object model; partial object model;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications Conference (SIU), 2013 21st

Conference_Location

Haspolat

Print_ISBN

978-1-4673-5562-9

Electronic_ISBN

978-1-4673-5561-2

Type

conf

DOI

10.1109/SIU.2013.6531265

Filename

6531265