Kechagias-Stamatis, OdysseasAouf, Nabil2017-02-012017-02-012016-06-09Kechagias-Stamatis O, Aouf N. Histogram of distances for local surface description. 2016 IEEE International Conference on Robotics and Automation (ICRA) 16-21 May 2016, Stockholm, Swedenhttps://doi.org/10.1109/ICRA.2016.7487402http://dspace.lib.cranfield.ac.uk/handle/1826/113793D object recognition is proven superior compared to its 2D counterpart with numerous implementations, making it a current research topic. Local based proposals specifically, although being quite accurate, they limit their performance on the stability of their local reference frame or axis (LRF/A) on which the descriptors are defined. Additionally, extra processing time is demanded to estimate the LRF for each local patch. We propose a 3D descriptor which overrides the necessity of a LRF/A reducing dramatically processing time needed. In addition robustness to high levels of noise and non-uniform subsampling is achieved. Our approach, namely Histogram of Distances is based on multiple L2-norm metrics of local patches providing a simple and fast to compute descriptor suitable for time-critical applications. Evaluation on both high and low quality popular point clouds showed its promising performance.Attribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/Article