GSHOT: a Global Descriptor from SHOT to Reduce Time and Space Requirements

This paper presents a new 3D global feature descriptor for object recognition using shape representation on organized point clouds. Object recognition applications usually require significant speed and memory. The proposed descriptor requires 57 times less memory and it is also up to 3 times faster than the local feature descriptor in which it is based. Experimental results indicate that this new 3D global descriptor obtains better matching scores in comparison with known state-of-the-art 3D feature descriptors on two standard benchmark dataset.This work was supported by the European FEDER funds, the Spanish Ministry of Economising and the Valencia Regional Government through the research projects DPI 2015-68087R and PROMETEO 20/3/085, as well as the pre-doctoral grant BES-2013-062864