Xtru3d: Single-view 3d object reconstruction from color and depth data

Abstract

3D object reconstruction from single image has been a noticeable research trend in recent years. The most common method is to rely on symmetries of real-life objects, but these are hard to compute in practice. However, a large class of everyday objects, especially when manufactured, can be generated by extruding a 2D shape through an extrusion axis. This paper proposes to exploit this property to acquire 3D object models using a single RGB+Depth image, such as those provided by available low-cost range cameras. It estimates the hidden parts by exploiting the geometrical properties of everyday objects, and both depth and color information are combined to refine the model of the object of interest. Experimental results on a set of 12 common objects are shown to demonstrate not only the effectiveness and simplicity of our approach, but also its applicability for tasks such as robotic grasping.