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Rotational Projection Statistics for 3D Local Surface Description and Object Recognition
2013
International Journal of Computer Vision
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
doi:10.1007/s11263-013-0627-y
fatcat:6ug4scszbngj7itgzghvffdera