Depth-assisted Real-time 3D Object Detection for Augmented Reality

Abstract

We propose a novel method of real-time object detection that can recognize three-dimensional (3D) target objects, regardless of their texture and lighting condition changes. Our method computes a set of reference templates of a target object from both RGB and depth images, which describes the texture and geometry of the object, and fuses them for robust detection.