DocumentCode :
1796314
Title :
Performance Evaluation of 3D Local Surface Descriptors for Low and High Resolution Range Image Registration
Author :
Ali Shah, S. Aamir ; Bennamoun, Mohammed ; Boussaid, Farid
Author_Institution :
Sch. of Comput. Sci. & Software Eng., Univ. of Western Australia, Crawley, WA, Australia
fYear :
2014
fDate :
25-27 Nov. 2014
Firstpage :
1
Lastpage :
7
Abstract :
Despite the advent and popularity of low-cost commercial sensors (e.g., Microsoft Kinect), research in 3D vision still primarily focuses on the development of advanced algorithms geared towards high resolution data. This paper presents a comparative performance evaluation of renowned state-of-the-art 3D local surface descriptors for the task of registration of both high and low resolution range image data. The datasets used in these experiments are the renowned high resolution Stanford 3D models dataset and challenging low resolution Washington RGB-D object dataset. Experimental results show that the performance of certain local surface descriptors is significantly affected by low resolution data.
Keywords :
computer vision; image colour analysis; image registration; image resolution; image sensors; 3D local surface descriptors; 3D vision; high resolution Stanford 3D models; high resolution range image registration; low resolution Washington RGB-D object dataset; low resolution range image registration; low-cost commercial sensors; performance evaluation; Accuracy; Image resolution; Kernel; Niobium; Robustness; Three-dimensional displays; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital lmage Computing: Techniques and Applications (DlCTA), 2014 International Conference on
Conference_Location :
Wollongong, NSW
Type :
conf
DOI :
10.1109/DICTA.2014.7008123
Filename :
7008123
Link To Document :
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