CORE: A Cloud-based Object Recognition Engine for robotics

Abstract

An object recognition engine needs to extract discriminative features from data representing an object and accurately classify the object to be of practical use in robotics. Furthermore, the classification of the object must be rapidly performed in the presence of a voluminous stream of data. These conditions call for a distributed and scalable architecture that can utilize a cloud computing infrastructure for performing object recognition. This paper introduces a Cloud-based Object Recognition Engine (CORE) to address these needs. CORE is able to train on large-scale datasets, perform classification of 3D point cloud data, and efficiently transfer data in a robotic network.