NDLI: Rotational Projection Statistics for 3D Local Surface Description and Object Recognition

Content Provider	Springer Nature Link
Author	Guo, Yulan Sohel, Ferdous Bennamoun, Mohammed Lu, Min Wan, Jianwei
Copyright Year	2013
Abstract	Recognizing 3D objects in the presence of noise, varying mesh resolution, occlusion and clutter is a very challenging task. This paper presents a novel method named Rotational Projection Statistics (RoPS). It has three major modules: local reference frame (LRF) definition, RoPS feature description and 3D object recognition. We propose a novel technique to define the LRF by calculating the scatter matrix of all points lying on the local surface. RoPS feature descriptors are obtained by rotationally projecting the neighboring points of a feature point onto 2D planes and calculating a set of statistics (including low-order central moments and entropy) of the distribution of these projected points. Using the proposed LRF and RoPS descriptor, we present a hierarchical 3D object recognition algorithm. The performance of the proposed LRF, RoPS descriptor and object recognition algorithm was rigorously tested on a number of popular and publicly available datasets. Our proposed techniques exhibited superior performance compared to existing techniques. We also showed that our method is robust with respect to noise and varying mesh resolution. Our RoPS based algorithm achieved recognition rates of 100, 98.9, 95.4 and 96.0 % respectively when tested on the Bologna, UWA, Queen’s and Ca’ Foscari Venezia Datasets.
Starting Page	63
Ending Page	86
Page Count	24
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	105
Issue Number	1
e-ISSN	15731405
Language	English
Publisher	Springer US
Publisher Date	2013-04-24
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Surface descriptor Local feature Local reference frame 3D representation Feature matching 3D object recognition Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence (incl. Robotics) Image Processing and Computer Vision Pattern Recognition
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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